{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Семинар 7. Визуализация данных. Знакомство с sklearn.\n", "\n", "Обратите внимание, что на семинаре 22 марта будет проверочная работа." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import scipy as sp\n", "\n", "import pylab as plt\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Квартет Энскомба\n", "\n", "Наборы данных имеют одинаковое среднее, дисперсию, коэффициент корреляции. " ] }, { "cell_type": "code", "execution_count": 501, "metadata": { "collapsed": true }, "outputs": [], "source": [ "data = np.array([\n", " [\n", " [10.0, 8.0, 13.0, 9.0, 11.0, 14.0, 6.0, 4.0, 12.0, 7.0, 5.0], \n", " [8.04, 6.95, 7.58, 8.81, 8.33, 9.96, 7.24, 4.26, 10.84, 4.82, 5.68]\n", " ],\n", " [\n", " [10.0, 8.0, 13.0, 9.0, 11.0, 14.0, 6.0, 4.0, 12.0, 7.0, 5.0],\n", " [9.14, 8.14, 8.74, 8.77, 9.26, 8.10, 6.13, 3.10, 9.13, 7.26, 4.74]\n", " ],\n", " [\n", " [10.0, 8.0, 13.0, 9.0, 11.0, 14.0, 6.0, 4.0, 12.0, 7.0, 5.0],\n", " [7.46, 6.77, 12.74, 7.11, 7.81, 8.84, 6.08, 5.39, 8.15, 6.42, 5.73]\n", " ],\n", " [\n", " [8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 19.0, 8.0, 8.0, 8.0],\n", " [6.58, 5.76, 7.71, 8.84, 8.47, 7.04, 5.25, 12.50, 5.56, 7.91, 6.89]\n", " ]\n", " ])" ] }, { "cell_type": "code", "execution_count": 502, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "MEAN: [ 9. 7.5] STD: [ 3.16 1.94] CORR: 0.816420516345\n", "MEAN: [ 9. 7.5] STD: [ 3.16 1.94] CORR: 0.816236506\n", "MEAN: [ 9. 7.5] STD: [ 3.16 1.94] CORR: 0.81628673949\n", "MEAN: [ 9. 7.5] STD: [ 3.16 1.94] CORR: 0.816521436889\n" ] } ], "source": [ "%precision 2\n", "for i in range(data.shape[0]):\n", " print \"MEAN: \", data[i].mean(axis=1), \"STD: \", data[i].std(axis=1), \"CORR: \", np.corrcoef(data[i])[0, 1]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Кроме того, решение задачи линейной ререссии дает для них одно и тоже уравнение:\n", "\n", "$y = 3 + 0.5x$\n", "\n", "Что же будет если их визуализировать?" ] }, { "cell_type": "code", "execution_count": 503, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(16, 4))\n", "for idx, X in enumerate(data):\n", " plt.subplot(1, 4, idx + 1)\n", " plt.scatter(X[0], X[1])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Корреляция между признаками\n", "\n", "Иногда бывает удобно посмотреть (например, видно линейно зависимые признаки)." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from sklearn import datasets" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "boston = datasets.load_boston()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Boston House Prices dataset\n", "\n", "Notes\n", "------\n", "Data Set Characteristics: \n", "\n", " :Number of Instances: 506 \n", "\n", " :Number of Attributes: 13 numeric/categorical predictive\n", " \n", " :Median Value (attribute 14) is usually the target\n", "\n", " :Attribute Information (in order):\n", " - CRIM per capita crime rate by town\n", " - ZN proportion of residential land zoned for lots over 25,000 sq.ft.\n", " - INDUS proportion of non-retail business acres per town\n", " - CHAS Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)\n", " - NOX nitric oxides concentration (parts per 10 million)\n", " - RM average number of rooms per dwelling\n", " - AGE proportion of owner-occupied units built prior to 1940\n", " - DIS weighted distances to five Boston employment centres\n", " - RAD index of accessibility to radial highways\n", " - TAX full-value property-tax rate per $10,000\n", " - PTRATIO pupil-teacher ratio by town\n", " - B 1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town\n", " - LSTAT % lower status of the population\n", " - MEDV Median value of owner-occupied homes in $1000's\n", "\n", " :Missing Attribute Values: None\n", "\n", " :Creator: Harrison, D. and Rubinfeld, D.L.\n", "\n", "This is a copy of UCI ML housing dataset.\n", "http://archive.ics.uci.edu/ml/datasets/Housing\n", "\n", "\n", "This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University.\n", "\n", "The Boston house-price data of Harrison, D. and Rubinfeld, D.L. 'Hedonic\n", "prices and the demand for clean air', J. Environ. Economics & Management,\n", "vol.5, 81-102, 1978. Used in Belsley, Kuh & Welsch, 'Regression diagnostics\n", "...', Wiley, 1980. N.B. Various transformations are used in the table on\n", "pages 244-261 of the latter.\n", "\n", "The Boston house-price data has been used in many machine learning papers that address regression\n", "problems. \n", " \n", "**References**\n", "\n", " - Belsley, Kuh & Welsch, 'Regression diagnostics: Identifying Influential Data and Sources of Collinearity', Wiley, 1980. 244-261.\n", " - Quinlan,R. (1993). Combining Instance-Based and Model-Based Learning. In Proceedings on the Tenth International Conference of Machine Learning, 236-243, University of Massachusetts, Amherst. Morgan Kaufmann.\n", " - many more! (see http://archive.ics.uci.edu/ml/datasets/Housing)\n", "\n" ] } ], "source": [ "print boston.DESCR" ] }, { "cell_type": "code", "execution_count": 73, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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CRIMZNINDUSCHASNOXRMAGEDISRADTAXPTRATIOBLSTAT
00.00632182.3100.5386.57565.24.0900129615.3396.904.98
10.0273107.0700.4696.42178.94.9671224217.8396.909.14
20.0272907.0700.4697.18561.14.9671224217.8392.834.03
30.0323702.1800.4586.99845.86.0622322218.7394.632.94
40.0690502.1800.4587.14754.26.0622322218.7396.905.33
\n", "
" ], "text/plain": [ " CRIM ZN INDUS CHAS NOX RM AGE DIS RAD TAX PTRATIO \\\n", "0 0.00632 18 2.31 0 0.538 6.575 65.2 4.0900 1 296 15.3 \n", "1 0.02731 0 7.07 0 0.469 6.421 78.9 4.9671 2 242 17.8 \n", "2 0.02729 0 7.07 0 0.469 7.185 61.1 4.9671 2 242 17.8 \n", "3 0.03237 0 2.18 0 0.458 6.998 45.8 6.0622 3 222 18.7 \n", "4 0.06905 0 2.18 0 0.458 7.147 54.2 6.0622 3 222 18.7 \n", "\n", " B LSTAT \n", "0 396.90 4.98 \n", "1 396.90 9.14 \n", "2 392.83 4.03 \n", "3 394.63 2.94 \n", "4 396.90 5.33 " ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = pd.DataFrame(boston.data, columns=boston.feature_names)\n", "data.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Но огромные таблицы, особенно если признаков очень много, сложно анализировать:" ] }, { "cell_type": "code", "execution_count": 508, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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CRIMZNINDUSCHASNOXRMAGEDISRADTAXPTRATIOBLSTAT
CRIM1.000000-0.1994580.404471-0.0552950.417521-0.2199400.350784-0.3779040.6220290.5795640.288250-0.3773650.452220
ZN-0.1994581.000000-0.533828-0.042697-0.5166040.311991-0.5695370.664408-0.311948-0.314563-0.3916790.175520-0.412995
INDUS0.404471-0.5338281.0000000.0629380.763651-0.3916760.644779-0.7080270.5951290.7207600.383248-0.3569770.603800
CHAS-0.055295-0.0426970.0629381.0000000.0912030.0912510.086518-0.099176-0.007368-0.035587-0.1215150.048788-0.053929
NOX0.417521-0.5166040.7636510.0912031.000000-0.3021880.731470-0.7692300.6114410.6680230.188933-0.3800510.590879
RM-0.2199400.311991-0.3916760.091251-0.3021881.000000-0.2402650.205246-0.209847-0.292048-0.3555010.128069-0.613808
AGE0.350784-0.5695370.6447790.0865180.731470-0.2402651.000000-0.7478810.4560220.5064560.261515-0.2735340.602339
DIS-0.3779040.664408-0.708027-0.099176-0.7692300.205246-0.7478811.000000-0.494588-0.534432-0.2324710.291512-0.496996
RAD0.622029-0.3119480.595129-0.0073680.611441-0.2098470.456022-0.4945881.0000000.9102280.464741-0.4444130.488676
TAX0.579564-0.3145630.720760-0.0355870.668023-0.2920480.506456-0.5344320.9102281.0000000.460853-0.4418080.543993
PTRATIO0.288250-0.3916790.383248-0.1215150.188933-0.3555010.261515-0.2324710.4647410.4608531.000000-0.1773830.374044
B-0.3773650.175520-0.3569770.048788-0.3800510.128069-0.2735340.291512-0.444413-0.441808-0.1773831.000000-0.366087
LSTAT0.452220-0.4129950.603800-0.0539290.590879-0.6138080.602339-0.4969960.4886760.5439930.374044-0.3660871.000000
\n", "
" ], "text/plain": [ " CRIM ZN INDUS CHAS NOX RM AGE \\\n", "CRIM 1.000000 -0.199458 0.404471 -0.055295 0.417521 -0.219940 0.350784 \n", "ZN -0.199458 1.000000 -0.533828 -0.042697 -0.516604 0.311991 -0.569537 \n", "INDUS 0.404471 -0.533828 1.000000 0.062938 0.763651 -0.391676 0.644779 \n", "CHAS -0.055295 -0.042697 0.062938 1.000000 0.091203 0.091251 0.086518 \n", "NOX 0.417521 -0.516604 0.763651 0.091203 1.000000 -0.302188 0.731470 \n", "RM -0.219940 0.311991 -0.391676 0.091251 -0.302188 1.000000 -0.240265 \n", "AGE 0.350784 -0.569537 0.644779 0.086518 0.731470 -0.240265 1.000000 \n", "DIS -0.377904 0.664408 -0.708027 -0.099176 -0.769230 0.205246 -0.747881 \n", "RAD 0.622029 -0.311948 0.595129 -0.007368 0.611441 -0.209847 0.456022 \n", "TAX 0.579564 -0.314563 0.720760 -0.035587 0.668023 -0.292048 0.506456 \n", "PTRATIO 0.288250 -0.391679 0.383248 -0.121515 0.188933 -0.355501 0.261515 \n", "B -0.377365 0.175520 -0.356977 0.048788 -0.380051 0.128069 -0.273534 \n", "LSTAT 0.452220 -0.412995 0.603800 -0.053929 0.590879 -0.613808 0.602339 \n", "\n", " DIS RAD TAX PTRATIO B LSTAT \n", "CRIM -0.377904 0.622029 0.579564 0.288250 -0.377365 0.452220 \n", "ZN 0.664408 -0.311948 -0.314563 -0.391679 0.175520 -0.412995 \n", "INDUS -0.708027 0.595129 0.720760 0.383248 -0.356977 0.603800 \n", "CHAS -0.099176 -0.007368 -0.035587 -0.121515 0.048788 -0.053929 \n", "NOX -0.769230 0.611441 0.668023 0.188933 -0.380051 0.590879 \n", "RM 0.205246 -0.209847 -0.292048 -0.355501 0.128069 -0.613808 \n", "AGE -0.747881 0.456022 0.506456 0.261515 -0.273534 0.602339 \n", "DIS 1.000000 -0.494588 -0.534432 -0.232471 0.291512 -0.496996 \n", "RAD -0.494588 1.000000 0.910228 0.464741 -0.444413 0.488676 \n", "TAX -0.534432 0.910228 1.000000 0.460853 -0.441808 0.543993 \n", "PTRATIO -0.232471 0.464741 0.460853 1.000000 -0.177383 0.374044 \n", "B 0.291512 -0.444413 -0.441808 -0.177383 1.000000 -0.366087 \n", "LSTAT -0.496996 0.488676 0.543993 0.374044 -0.366087 1.000000 " ] }, "execution_count": 508, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.corr()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Поэтому давайте визуализируем ее!" ] }, { "cell_type": "code", "execution_count": 74, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 74, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "correlation = data.corr()\n", "plt.figure(figsize=(6, 6))\n", "plt.pcolor(correlation)\n", "plt.xticks(np.arange(0.5, len(data.columns)), data.columns, rotation='vertical')\n", "plt.yticks(np.arange(0.5, len(data.columns)), data.columns)\n", "plt.colorbar()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Функция colorbar строит соответствие цвета и значения. Обратите внимание, что функция pcolor принимает на вход просто некоторую матрицу. Например, можно (зачем-то) визуализировать все признаки:" ] }, { "cell_type": "code", "execution_count": 55, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 55, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.pcolor(data.values)\n", "plt.colorbar()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Это называется \"hotmap\" – чем больше значение, тем \"горячее\" цвет." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Сэмплирование?\n", "\n", "Хочется посмотреть на признак, но данных очень много. Давайте возьмем случайное подмножество точек и будем смотреть на них." ] }, { "cell_type": "code", "execution_count": 56, "metadata": { "collapsed": false }, "outputs": [], "source": [ "points = np.random.choice(data.AGE, 100)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Посмотрим на признаки повнимательнее\n", "\n", "Как визуализировать один признак?\n", "\n", "Например, **набор точек на прямой**" ] }, { "cell_type": "code", "execution_count": 511, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 511, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(15, 1.5)), plt.grid(True, axis='x'), plt.yticks([])\n", "plt.scatter(points, np.zeros(points.shape[0]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Недостатки: не видно плотности точек в некоторых участках.\n", "\n", "Что с этим можно сделать? Например, для каждой точки выберем случайно вертикальную координату (**jitter**)" ] }, { "cell_type": "code", "execution_count": 512, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 512, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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Uhikte5N2AAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(15, 1.5)), plt.grid(True, axis='x'), plt.yticks([])\n", "plt.scatter(points, np.random.randn(points.shape[0]), marker='*', s=50)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Можно построить **гистограмму**:" ] }, { "cell_type": "code", "execution_count": 513, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(array([ 1., 6., 14., 6., 7., 8., 3., 9., 13., 33.]),\n", " array([ 7.8 , 17.02, 26.24, 35.46, 44.68, 53.9 , 63.12,\n", " 72.34, 81.56, 90.78, 100. ]),\n", " )" ] }, "execution_count": 513, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.hist(points)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "При этом если признаков несколько, то можно их все построить на одной гистограмме:" ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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SwRn0klRwBr0kFZxBL0kFZ9BLUsEZ9JJUcAa9JBWcQS9JBWfQS1LBGfSSVHAGvSQVnEEv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\nDHpJKjiDXpIKzqCXpIL7/7zBBmwEUN4NAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "random_indexies = np.random.choice(data.index, 100)\n", "\n", "tot_points = data['RM'][random_indexies]\n", "other_points = data['DIS'][random_indexies]\n", "free_points = data['LSTAT'][random_indexies]\n", "\n", "plt.hist([tot_points, other_points, free_points])\n", "plt.legend(('RM', 'DIS', 'LSTAT'), loc='upper right')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Но вернемся к одному признаку. \n", "\n", "Альтернатива диаграмме — **KDE** (Kernel Density Estimation).\n", "\n", "Значение графика в точке: $f(x) = \\dfrac{1}{nh}\\sum_{i=1}^n{K(\\dfrac{x - x_i}{h})}$" ] }, { "cell_type": "code", "execution_count": 515, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from scipy.stats import gaussian_kde" ] }, { "cell_type": "code", "execution_count": 516, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 516, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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Wwq5dsGEDVFf3vI+hQ32z0XPPhblzITv7YJTk8LN9O3zyk/Daa35+9mx49lkoLc1sXNKn\nqLWVkkd6VVbC7bf7pNHS0r7cDE4+2TfvPOUUX+k6ZMi+P6+hwV+tvPWWv931v/8L69Z9cL2iIvjH\nf4SLLvJXJroiOTCrVvnE8e67fv6ss+CJJ6CgILNxSZ+j5KHkkR51dXDzzf4RpJFI+/IZM+Dyy2H+\nfBiWpuHFNm+G557zLX5eeAGamjq/P3YsXHyxHxp84sT07PNw8Oc/+++prs7PX3SRH3YkHM5sXNIn\nKXkoefSOc/DII/Dtb/tbVa0+9jH43vd8f4CD2fu4oQH+9CdYuND/2zFxga8b+cpX/FWJbmt1Lx6H\n738ffvAD/32CH3Lk+uvVc1x6pOSh5HHgqqp8M87nnmtf9pGPwI9+5G9NHWq7dsFvf+ublbber281\ndKi/Ern8cl2NdFRd7a8wFi3y83l58PDDcP75mY1L+jwlDyWPA7NwIfzzP7ePqjpyJPzHf8DnP983\n/lpduRJ+8Qv/Q7hzZ+f3zj4bvvpVX9l+OA+t8dhj/jtsPT7Tp8Pjj/t/RfZByUPJIzUtLfCNb8C9\nHR7mePHFcNddMHhw5uLqSXOzr/C97z545ZXO740a5a+cLrsMxo/PTHyZUF0N//Iv/iqt1T/9k/9O\n8/MzF5f0K0oeSh77b/NmfztjyRI/X1Li/7o/r588pHHlSp9EHn64vVIY/JXS2Wf7upFPfGLgVhDH\nYv6RsTfc0F7+khJ/TD7zmczGJv2OkoeSx/5ZssQ34WytFD/5ZH+LY+zYvW/XFzU0+L+677uvPRG2\nKi31dQCXXgrHHts3bsH1lnO+k+b11/umuK3OP98/b3z48MzFJv2WkoeSx7498YS/rdHaJPbKK+GO\nOwbGX+jLl/urp1/9yndO7Gj6dPjCF+Bzn/PDpPQ3zvnOfbfcAn//e/vyiRN9k+q5czMXm/R7Sh5K\nHnu3YAF8/ev+hygQgLvv9sljoGls9M+pePBB3/Ko6zlxwgn+1s6558K0aX37iqShwVeG33EHrFjR\nvry4GK67Dq6+2j9zXKQXlDyUPLrnnO/0d/PNfr6gwN+mOhz+Wt20CR591PdfWbnyg+9Pngwf/7iv\nJzntND+0SqYlEv7q4te/9q+OdTqDBsFVV/m+OH2xUYP0S0oeSh4f5JxvjXP33X5+6FA/DPesWZmN\n61Bzzv/l/vjj/lVe/sF1wmE/WONpp/k+LrNn+7/wD4X6ej9cy3PP+aumqqrO748cCddc45slawh1\nSTMlDyWPzhIJ/1dqa1PcceP8ECBTpmQ2rr5gzRpf8fz0036k4Hi8+/WmTPGV7ccc44dnmTzZ1zP0\n5gplzx6fvFat8pX8r78Oy5b5FlQdBQJ+PKorrvBXR1lZB75Pkb1Q8lDyaJdI+E5j99/v5ydN8vf/\n+2OLqoOtttYfm0WL/F//77yz722GDYPRo/0VQXGxf+Xl+WFTsrJ8MopGff3L7t2+897777c/86Qn\nWVl+GJjPftYPw6LWU3IIKHkoeXjOwde+5puvgv/r+aWXfEc62bedO+GNN/wVwZIlPpls2nRw9pWd\n7W8hzpkDZ57pb5lp1Fs5xJQ8lDx84vjXf4U77/Tz06b5v6hHjsxsXP3d7t2wdq0fQn79el8nUVnp\nryJ27fIJp6mp82COwaC/vTV4sH+NGgVjxvge8NOmwVFHwdSpA6OZtPRrSh5KHr7H8Q9/6KcnToS/\n/lVXHIeSc/6WVTDYt5sAi3Sg5HG4J4877vBXHeArx//618NrnCcROSBKHodz8njoIT8MB/hK1lde\n8ZXkIiL7oORxuCaPp5/2LXPicd8H4K9/9U1LRUT2Q2+TRyCdwcgh8ve/+/Ga4nFfOfvMM0ocInJI\nKXn0N+XlftjxpiZfQfvYY75ntIjIIaTk0Z9s2eLHpmp9ctz99/tEIiJyiCl59Bf19X64io0b/fwP\nfgBf+lJmYxKRw5aSR38Qi8EFF/ixkAAuvxy++93MxiQihzUlj76uddiRv/zFz59zjn96nDqjiUgG\nKXn0dbfdBj//uZ+eNcs/fjUUymxMInLYUz+PvuzRR+Hzn/fT48bBa69pvCoRSQt1EhyoyePll+Gj\nH/WD7hUVwauv+mdLiIikgToJDkRr18J55/nEEQrB73+vxCEifYqSR1+zbZuvFG/ty/Hzn8MZZ2Q2\nJhGRLtKSPMxsrpmVm9laM/tOD+vcbWbrzGy5mR23r23N7EYzqzSzpcnX3HTE2qc1NfkrjooKP3/D\nDe0DH4qI9CG9brZjZgFgAXAm8D6wxMyedM6Vd1hnHjDROTfZzE4G7gPm7Me2dzjn7uhtjP1CIgGX\nXOKfrQ1w0UVw882ZjUlEpAfpuPI4CVjnnNvonIsCC4Fzu6xzLvAwgHPudaDIzIbvx7aHT2eG666D\nxx/306edBg88oL4cItJnpSN5jAY2d5ivTC7bn3X2te1VydtcvzCzojTE2jfddx/86Ed+eto0+MMf\n/HOuRUT6qExVmO/Pn9T3AEc6544DqoGBefvq6afhyiv99LBh8OyzUFyc2ZhERPYhHV2Vq4BxHebH\nJJd1XWdsN+uEe9rWObetw/KfA0/3FMBNN93UNl1WVkZZWdn+xp5Zb7wB8+f7+o7cXJ9Ijjgi01GJ\nyAC0ePFiFi9enLbP63UnQTMLAmvwld5bgDeAC51zqzuscw5wpXPu42Y2B/iJc27O3rY1sxHOuerk\n9t8AZjvnPt/N/vtnJ8GKCjjlFN80NxCAP/4RPvnJTEclIoeJ3nYS7PWVh3MubmZXAc/jb4M9kPzx\nv8K/7e53zj1rZueY2XqgAfji3rZNfvSPkk16E8AG4IrextpnbN0KZ5/tEwfAggVKHCLSr2h4kkNt\nzx4oK4O33vLz118Pt9yS0ZBE5PCjsa36U/KIRPwVxvPP+/lLL4Vf/lJNckXkkNPYVv1FPA4XX9ye\nOObN84+RVeIQkX5IyeNQcA6uvto/iwN8Rfnjj0NWVmbjEhE5QEoeh8L3vgf33uunZ8yAZ56B/PzM\nxiQi0gtKHgfbbbfBv/+7n54wAZ57DoYMyWhIIiK9pQrzg2nBAn+7CvwTAF9+GSZOzGxMIiKowrzv\n+tnP2hNHaSm8+KISh4gMGEoeB8MvfgFf/aqfHjzYt7CaPj2zMYmIpJGSR7o98ABcfrmfLiqCF16A\n44/PbEwiImmm5JFO99wDX/6yb5pbWOgrx088MdNRiYiknZJHutx5Z/vQ6kVFPnGcfHJmYxIROUiU\nPHrLObjxRvjmN/38kCHwP/8Dc+ZkNi4RkYMoHc/zOHwlEvD1r8NPf+rnhw71dRzHHpvZuEREDjIl\njwPV3OwHNmwdcmT8eN+qasqUjIYlInIoKHkciJ074dxz4ZVX/Pz06T5xjO766HYRkYFJdR6pWr8e\nPvSh9sTxkY/4nuNKHCJyGFHySMWiRb4F1Zo1fv5zn/N1HBqrSkQOM0oe+8M5Xyl+1ln+lhXAtdfC\nb34DOTmZjU1EJANU57EvDQ1+qJFf/crPZ2f74Ue+8IXMxiUikkFKHnuzZg185jOwYoWfHzUKfv97\ndf4TkcOeblt1xzk/RtWsWe2J4/TTYdkyJQ4REZQ8Pmj3bl8R/uUvQ2Ojf8b4ddf5prjDhmU6OhGR\nPkG3rbp6+GH/fHGAESPgkUfgox/NbEwiIn2MniTYVTwOH/sY5OXBgw/6IUdERAaY3j5JUMmjO/X1\nUFDgb1mJiAxASh59+RnmIiJ9lJ5hLiIih5ySh4iIpEzJQ0REUqbkISIiKVPyEBGRlCl5iIhIypQ8\nREQkZUoeIiKSMiUPERFJmZKHiIikLC2j6prZXOAn+GT0gHPu9m7WuRuYBzQAlzrnlu9tWzMrBn4L\njAc2ABc452rTEe/eRKNRKioq2L27jsGDC5k4cSJZWVkHe7dEo1HKy8t5++0V1NRUM3z4CI45ZibT\npk1r239rbNu376SubjeFhYMpLR3SKcZ9xd/1/ZEjR/Lqq6/y/vs1jBo1nLKyMvLy8mhsbOTFF1/k\n739fwrp15QwaNJjjjz+aE044gffe28iWLe8Ti8UJhYKMHDmKY489mmnTpgF0W46JEyeyadOmfR7X\nrvGNGzduv7crLy/n//7vHWpqahg+fDgzZhxFKBSitrZ+v49X6/6qq7eyZs1qIMjYsaPajsvevr/W\nzwmHQ1RWVrJ1645Ox7Sj2tpaFi5cyIYNlUyYMIb58+eTl5eX0rnX03fdXZkqKiq6PTYNDU3dHueO\n8/n5uUSjUdauXQ/AlCmTyMrKatu2u3Os4zlQUlJKQUEeTU0tmBm5udk0NjYTCoXaPqv1O8rLK6Cx\ncQ+FhYMpKhpENBpl1aryTnE753jnnZWsWrWS3Nx8Zs06lg996EO88cYbbefxhz/8YcrLy3n88SfY\nuHEz48eP5VOf+gRVVVU888yfqa7eQjwewyxEdnYWRUVFmAUoKSlh5syjWLx4MRs3VjNx4hhuvfVW\nxo0b1+P3cLjq9dhWZhYA1gJnAu8DS4D5zrnyDuvMA65yzn3czE4G7nLOzdnbtmZ2O7DDOfcjM/sO\nUOycu7ab/adtbKvq6moeeuh5amtHEAgMJZHYRlFRNZdcchYjRoxIyz562u+CBY/x0kubqawcTjw+\nmGCwkjFj6jj99AlcddUFADz00PNUVRWwYkUdzc3N5OTsYubMIxg9OsIll5zVtk5P8Xct35YtS3n5\n5T9TWPhhsrOn4twmiopWc9llp3LPPS/yzjtxdu2qxrljgGEEApsIBJYwaFApzc3jiUZ3Eg5PoKio\ngPHjI8yeHQKiLFmyk8rKQuLxMQSDuxk27F0GDYoxc+ZcCguP6PG4do2vrm4N69b9ncmTT9vndgsW\nPMaiRe9SVeWIx48EAgSDFQwb1kI4XIxz48jJyWHmzEJGj97T7fFq3d/gwZN44411NDePJCtrEKWl\nUYYO3cDtt1/GMccc0+331/o527btYtGip4hGpzJixDGEQtUUFa3utO2iRYv46lfvoaHhBMwm4lwF\nOTmvc8YZUxk69Mz9Ovd6OlfnzTuOP/95eacyrVixmPr6YWzdOph43AGVBIPNjBmTy+zZ80gkdnQ6\nzh2PeyBQypIlr1Bd/S5DhpwMNLFz5+uMGDGd2bNPJS+v+QPnmD+XN1BZWUgkMoiGhpVAPgUFw3Gu\nlqamKgoKjqa0NEx9/VKGDBlLdnYOzc257NpVRXHxJLKzw0QiNWzduo54fBAwCUgAG4jHN9LQMAjn\njicQCJOdvZJY7F3Gjj2bgoKZtLSsp7r6SWpro7S0nAJMxrn1JBIv49xwnJuO/7mpB47A/20aBo7A\nbA/OLQGOxux4zDYSDC7i3//9fL71rW8d4P/wvinjAyOa2RzgRufcvOT8tYDrePVhZvcBLznnfpuc\nXw2U4b+5brc1s3LgNOdcjZmNABY756Z1s/+0JI9oNModdzwKnEFx8Zi25bt2VQKL+OY3LzwoVyDR\naJT/+I9H+N//raOy8kTC4eMJh/OJRHYRifyVMWPe4yMfySMYDAFn8OabW4Bp5OUV09joYzvxxFOB\nlwAIBs/qNv6rr/4M//Vfv2srXyTSxL33/iex2Fzy8mJMnz4bsxA1NW+wbNn1FBZ+laqqJzH7JqHQ\nsbS07CIe3whUYXYPubnnEAyejRnk5hqDB79HNFqO2dtkZc0jO/sMwuFiWlp2s2XLXRQVTWH69HGc\nffbJBIOhDxzXrsc/Ho/ywguP0tQ0i9zcej72sdk9buePXy2VlUHC4U8TDo9i8+Yq4vEq4E1KS2Mc\ne+yVNDfvAco58cSRwKJOx6t1f/X1M3j77V9TUnI5gwZNIxLZBZQzbFg+gcADPPHErZ2uIjrGnZ8/\nhHvvvQ74CuHwEUA106dPYOfO1cDPeeKJW4lGo8yefRlm32Hw4NnJT0lQUfEScDc33PAwublFez33\nejpXt2/fwMsv38mpp/4LpaVHEI9Hef75X7Fy5Qhqa7czatQ8wuEhbNr0NonEy5SUjGLy5B0EAiGa\nm08iN7eeM844jkWLHqepaRbZ2bU4F6eiohDn8sjKeiW5/5Mwq2HSpBzOPvtk6uqq286xn/xkYfJc\nPoKsrFPYseNZamtPALJw7h0ACgpmAn8F6ikuPoMdO/7IkCGnk5OzkUjkQ2RlGZHIe+zYEcS5nYRC\nWxg9+gqcUP3EAAARo0lEQVQqKzdRV7eUaHQj2dkBSkquIRarY9u22wgGP0ZRUYR/+IePsnp1BatX\nLyCRmEZh4SUEAvnU1v6VeDwKPI9PRB8BsoC7gQuBkcArwErgfKAOsyJyc08gEnkNs2+zfv1vB9QV\nSF8YGHE0sLnDfGVy2f6ss7dthzvnagCcc9XAQX2MX0VFBbW1Izr9ZwQoLh5Dbe0IKioqDtp+N25M\n0Ng4FrMjCYfzAQiHizGbRGPjMFasqGHDhhxisWyamgrJyysGIC9vDE1NI4jFWti4McGGDTk9xr94\n8eJO5VuzZgnNzUcyePBsotFC6uu3ARCLbaep6WR2796Ac8cTCh1PIpEACnGuEJhMIjGLeHwzWVlT\ngALi8RwaG4Ps2TOS+vopRKNhwmEfYyJRTSIxE+emsnNngm3btnV7XLse/23bKmhqGkFJyUyamgr3\nup0/foOAaYTDY2hubgYG4Vwukcg0IpGx1NdXkJdXTFNTIbFYNhs25LBxY+ID+4vFGmhpOYqsrHFt\n30M0Wkh29lBqa/3tjK7fX2vca9Ysprn5KAoKZhIO5xON5lJfX09Jycy2bRcuXEhDwwkdEgc0NzcT\nDp9ALDaHJUsWfuC763ru9XSuxmLZ1NYeRSzW0lam7dsLcW4UicQ4EokQzc3NmE0gGJxKNBqmsrKO\n7dtz2o7zmjVL2o77jh0hqqqagWEUFExhz54c9uxJJH/8R7R9nx3PMf9dDMNsEonETlpaSgkEJuJc\nCdHoMOLxQoLBwcTjg2huDhOPG4nEVBobW9izZwgFBVNoaGikoSGXSCQPmAJMo65uFfF4IfH4SJyb\nAowiGq0gGl2Jc9MJBo+nuXkwGzasYfv2d3DuRMxmEY9vJRrdQiJRAJwITAAcPln4c8b/DI4D4sAY\nYBYwHIgTj9eQnX0q8fgZXHfddUi7TD1J8ECyXY+XFzfddFPbdFlZGWVlZSl/+O7ddQQC3T/4KRAo\npba2PuXP3N/9RiLZxOPFQHaXdwuIxwvZsydOXl4RjY3NmA3qtIZZKY2N9UQiYaCox/i3bHmbQODY\ntmW1tTuBUW37iUT8D05jYw3OTaClpQI4qcu+cnGuDhhLLLYmuTQb5xqJxQIkEtk4N4J4vH2bWKwO\nGEEikUssFqGpqaVTXK3Htevxb2ysw2xocr8Fe90uEskmFqNt/VgsDoRIJBxQRDxuRKP1nT4rEhmE\nWeID+2tq2ojZWOIdC5E8PmZj2bJlW6dj0jHu2toa/I9Qq2yi0Vhyv37bDRsqMTu602e0xmt2JDt2\nrOr0XnfnXk/nqj8/xtLYWN9Wpni8OPl9FBOLxYAg/r99KfF4JZFIgOzsorZjU1u7DrPxAMTjOUQi\ndbSel4nEIPytI39MYrH6tu+l9Rzz53IhMIhYrBrnSvE/zkGgAHDE4y0kEoNwrpFodDcwilhsN6HQ\n0OR+HbFYNs45nMsDSolEanFuDFCAc804FyKRqCcW24n/ezMEDKKhoZ5IpA6zsThXTDzemIw5N7lO\nCbAnOb0bnyxa8D9JBgxNru/jc671vJvEe+/97QPHvD9ZvHjxB/746Y10JI8qOv+PGZNc1nWdsd2s\nE97LttVmNrzDbautPQXQMXkcqMGDC0kkNnX7XiKxnaKig3O5OnhwIeFwC8HgLvxJ3NEegsE6CgqC\nZGXVkpeXg3M7O63h3Hby8sYRDkfoqT1BIrGdkSOHUVHR/sNXVDSE9ou+PYTDQwDIyxuO2atkZ5cS\njW7osq+m5KXuZkKh1tsoLZhBKJQgHm8BqgkGi9u2CYUKgZUEArmEQlFyc9sTZMfj2vX45+UV4tym\n5H73kJs7pMftwuEWQiFwbltyn0EgQiBgxOO1BIO1ZGWN7vRZ4XA9Zs0f2F9u7hCcW0MwGOz0PYTD\nQ3BuMyNHdj4POsZdVDQc6HgOtZCVlZfcr982FmvGuc5XEq3xOvcuJSWjOr3X3bnX07nqz4/N5OVN\nbCtTMLiZYLAE2EUoNA7/Ix4BthMMGuFwgmCwtu3YFBUNabvKCwabCYcdzc2tCaIeaD1mezp9n63n\nWDj8PsFgHVBPKFSI2Xr8j3Ec/6PdQjCYTTxej1kjWVmDgVWEQiUEAjuT+zVCoRbMQpg1AtsJh4cm\nk/0ezBoxayQQmEQoNASoAI4H6snPH0Q4XIhz7wMFBIPDgRygFogBO5LHIIZPKJX4qwyXfG3DJ7t6\nzBxmrefreo44ovN30990/cP65ptv7tXnpeO21RJgkpmNN7MwMB94qss6TwEXQ1sdye7kLam9bfsU\ncGly+hLgyTTE2qOJEydSVFSdvM/cbteuSoqKqpk4ceJB2+/48QHy8jbj3LtEIg0ARCK7cG49eXlb\nmTlzOBMmNBMKtZCbW0dj4y4AGhsryc2tJhTKZvz4ABMmNPcYf1lZWafyTZ06m5ycd9m9ewlZWXUM\nGuT/6guFSsnNfZ3BgydgtoxYbBmBQAB/D7gOWEcgsJRgcCzR6Fp8gmsmLy9OQcEWBg1aS1ZWJFlX\nAIHACAKBFZitYciQAEOTj/Xtely7Hv+hQyeSm1vNjh0ryM2t2+t2/vjVA+VEIpXk5OTg//M3EQ6X\nEw5vZtCgiTQ27iI3t45QqIUJE5oZPz7wgf2FQvlkZ68mGt3U9j1kZdXR0rKNoqLVH7iq7Rj31Kll\n5OSsZs+eFUQiDWRlNTFo0CB27FjRtu38+fPJz3+L3buXtH1GTk4OkchbhEKvMXv2/A98d13PvZ7O\n1VCohaKi1YRC2W1lKi2tw+z9ZGOHGDk5OTi3gXh8DVlZEcaMKaS0tLntOE+dOrvtuJeUxBg9OgfY\nyp49aykoaKagIMCePSuA6rbvs+M55r+LrTi3nkBgCNnZ20kkKjDbQVbWVoLBOuLx3QSD9eTkRAgG\nHYHAGvLysiko2MmePWvJz88jP7+JcLgR356mnMLC6QSDdQSDWzBbC7xPVtZEsrJmYLaKeHwZOTm7\nmTBhKqWlR2P2Js4tJRgcRlbWSAKBPcCb+MpxA7bgK8zL8cltEz6pVAJLgRogSDA4nJaWlwkGF3Hr\nrbci7dLyJMFkc9u7aG9ue5uZXYGv/L4/uc4CYC6+qe4XnXNLe9o2uXwI8Bj+imUjvqnu7m72fZBa\nW5Um/+rLRGurIoLBqv1obbWTmTOP7KG11Qfj71q+LVuWdWhtNQXnNu+ltdVQAoHNPbS2ymf8+Gg3\nra1GEwzWdmltNaHH49o1vrq6tR1aAe19u46trWKxIzEzgsF3k62tBuPc+H20tmrfX+fWVvmUlsZT\naG21k0WLnk62tjqaUKhmH62tjsS5d7u0ttr3udfTudq5tZUvU3trq6LkLazNBIMtydZWc0kkdnY6\nzh2Pu1kJb775KtXV71JcfDJm7a2tTjzxI+Tnt+yjtVVBsrVVAfn5w4GOra2yqK9fxpAhYwmHc2hp\n2VdrqziwsUNrq+MIBLK7tLaaQUtLRZfWVpNwrqKH1lYT8D8vYWBCsrXVm/jWVsditlmtrXravr8/\nwjXdj6FtbSNfW1tPUdGgQ97P4513VlBdXcOIEcM5+uju+3ns2LGL2tpdFBUVU1JS3G2/hZ7i7/p+\naz+PLVu2MXLk0A/083j99TdZs6acoqLBHHvsTE444QQ2bNjEli1VxGIJQqEAI0eObuuTAnRbjtZ+\nHvs6rl3ja+1vsD/btfct8H0Cpk+fRigUoq5uz34fr9b91dRso7x8FWYhxowZud/9PGpr68nKClJZ\nWcm2bbs6HdOOWvt5bNr0PuPGjerUz2N/z72evuvuylRRUdHtsWlsbO72OHecz8vLIRqNsm6dv902\nebLfT+u2PfXzaD0HSktLyM/Po7k5ghnk5GTT1NRCKBRq+6zW7yg/39dbFBUVU1hYQDQaZfXqNZ3i\nds6xYsVKVq5cRX5+Pscdd0xbP4/W87i1n8fvfvcEmzZVMW7caD75Sd/P409/+gtbtmwhkYhilpXs\n51GIWZCSkhJmzJjG4sWL2bx5K0ccMWrA9vNQ8tAzzEVEUtYXmuqKiMhhRslDRERSpuQhIiIpU/IQ\nEZGUKXmIiEjKlDxERCRlSh4iIpIyJQ8REUmZkoeIiKRMyUNERFKm5CEiIilT8hARkZQpeYiISMqU\nPEREJGVKHiIikjIlDxERSZmSh4iIpEzJQ0REUqbkISIiKVPyEBGRlCl5iIhIypQ8REQkZUoeIiKS\nMiUPERFJmZKHiIikTMlDRERSpuQhIiIpU/IQEZGUKXmIiEjKlDxERCRlSh4iIpIyJQ8REUmZkoeI\niKRMyUNERFLWq+RhZsVm9ryZrTGz58ysqIf15ppZuZmtNbPv7Gt7MxtvZo1mtjT5uqc3cYqISHr1\n9srjWuBF59xUYBFwXdcVzCwALADOBmYAF5rZtP3Yfr1zblby9bVextlvLV68ONMhHFQqX/82kMs3\nkMuWDr1NHucCDyWnHwLO62adk4B1zrmNzrkosDC53b62t17GNiAM9BNY5evfBnL5BnLZ0qG3yWOY\nc64GwDlXDQzrZp3RwOYO85XJZQDD97L9hOQtq5fM7CO9jFNERNIotK8VzOwFYHjHRYADvtfN6q6X\n8bRuvwUY55zbZWazgD+a2XTn3J5efr6IiKSDc+6AX8Bq/NUDwAhgdTfrzAH+0mH+WuA7+7t98r2X\ngFk9vOf00ksvvfRK/dWb3/99Xnnsw1PApcDtwCXAk92sswSYZGbj8VcU84EL97a9mZUCO51zCTM7\nEpgEvNtdAM451Y2IiBxilvzr/cA2NhsCPAaMBTYCFzjndpvZSODnzrlPJNebC9yFr2N5wDl32z62\n/zTwfSACJID/55x79oADFRGRtOpV8hARkcNTv+5h3lPnw/7KzMaY2SIzW2lm75jZ15PL96szZn9g\nZoFkK7qnkvMDqWxFZva4ma1OfocnD7DyXZcs19tm9mszC/fn8pnZA2ZWY2Zvd1jWY3mS5V+X/H7P\nykzU+6+H8v0oGf9yM3vCzAo7vJdS+fpt8thH58P+KgZ80zk3AzgFuDJZpn12xuxHrgFWdZgfSGW7\nC3jWOXcUcCxQzgApX7LO8ivA8c65Y/AtNS+kf5fvQfzvR0fdlsfMpgMXAEcB84B7zKyv17d2V77n\ngRnOueOAdfSifP02ebD3zof9knOu2jm3PDm9B98abQz71xmzzzOzMcA5wC86LB4oZSsETnXOPQjg\nnIs552oZIOUD6vB1kPlmFgJygSr6cfmcc68Au7os7qk8nwIWJr/XDfgf3pMORZwHqrvyOededM4l\nkrOv4X9f4ADK15+Tx946H/Z7ZjYBOA7/Be+tM2V/cifwb/hmgq0GStmOALab2YPJ23L3m1keA6R8\nzrldwI+BTfikUeuce5EBUr4Oeur43PX3por+/3vzJaC1IVLK5evPyWPAMrMC4HfANckrkK6tGvpd\nKwcz+zhQk7yy2tvlcL8rW1IImAX81Dk3C2jA3wLp998dQLLJ/DeA8cAo/BXIRQyQ8u3FQCsPAGb2\nXSDqnHv0QD+jPyePKmBch/kxyWX9WvKWwO+AR5xzrf1masxsePL9EcDWTMXXCx8GPmVm7wKPAmeY\n2SNA9QAoG/gr383OuTeT80/gk8lA+O4ATgRedc7tdM7FgT8AH2LglK9VT+WpwncpaNVvf2/M7FL8\n7ePPd1iccvn6c/Jo63xoZmF858OnMhxTOvwSWOWcu6vDstbOlNBzZ8w+zTl3vXNunHPuSPx3tcg5\n90/A0/TzsgEkb3VsNrMpyUVnAisZAN9d0hpgjpnlJCtSz8Q3fOjv5TM6Xwn3VJ6ngPnJFmZH4Dsu\nv3GoguyFTuVL9rn7N+BTzrmWDuulXr7edE/P9AuYiz+p1wHXZjqeNJTnw0AcWA4sA5YmyzgEeDFZ\n1ueBwZmOtZflPA14Kjk9YMqGb2G1JPn9/R4oGmDl+zd8QnwbX5mc1Z/LB/wGeB9owdflfBEo7qk8\n+JZJ6/ENWc7KdPwHWL51+A7ZS5Ovew60fOokKCIiKevPt61ERCRDlDxERCRlSh4iIpIyJQ8REUmZ\nkoeIiKRMyUNERFKm5CEiIilT8hARkZT9f9GS2quqUWShAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "density = gaussian_kde(points)\n", "xs = np.linspace(min(points)-0.01, max(points)+0.01, 100)\n", "plt.plot(xs, density(xs), linewidth=2.5, color='red')\n", "plt.scatter(points, np.zeros(len(points)), s=50, alpha=0.4)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Однако здесь аналогичные проблемы, что и у гистограммы: выбор \"шага\"" ] }, { "cell_type": "code", "execution_count": 517, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 517, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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AVSkoqzEmU6xZAw0NbrmsLK1FGYpSETzGAztj1iuJBoBEaXbFpxGRycAc4FXvqTGqWgOg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\nMX1mwcMYY0yf/X8hc1liJjydYgAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "density = gaussian_kde(points, bw_method=0.1)\n", "xs = np.linspace(min(points)-0.01, max(points)+0.01, 100)\n", "plt.plot(xs, density(xs), linewidth=2.5, color='red')\n", "plt.scatter(points, np.zeros(len(points)), s=50, alpha=0.4)" ] }, { "cell_type": "code", "execution_count": 518, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 518, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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G129m/xPY4u4vFti3ogNLOp3mP/yH7wEfZPbsxuH1Z860Ac/xZ39270XpuaTT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\nn+Tw4RMsWXLFtL2ORYFlHFE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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "density = gaussian_kde(points, bw_method=4)\n", "xs = np.linspace(min(points)-0.01, max(points)+0.01, 100)\n", "plt.plot(xs, density(xs), linewidth=2.5, color='red')\n", "plt.scatter(points, np.zeros(len(points)), s=50, alpha=0.4)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Ящик с усами (диаграмма размаха)\n", "\n", "![](http://i.imgur.com/7c7DSDg.png)\n", "\n", "Первый ($Q_1$) и третий ($Q_3$) квартили — концы ящика, медиана (второй квартиль) — вертикальная линия внутри ящика, усы — $Q_1 - 1.5 * IQR$ и $Q_3 + 1.5 * IQR$, $IQR$ = interquartile range, $Q_3 - Q_1$, остальные точки — выбросы. Иногда усы строят чуть [по-другому](https://en.wikipedia.org/wiki/Box_plot)." ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "collapsed": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/usr/local/lib/python2.7/site-packages/ipykernel/__main__.py:1: FutureWarning: \n", "The default value for 'return_type' will change to 'axes' in a future release.\n", " To use the future behavior now, set return_type='axes'.\n", " To keep the previous behavior and silence this warning, set return_type='dict'.\n", " if __name__ == '__main__':\n" ] }, { "data": { "image/png": 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jy8p/PzqdDlmWMT8/DzDIl8OMWx65HegsK4/siYhnrLKvyyNm9nOqUpaoShzDFC2PiJ+/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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "_ = data[['RM', 'DIS', 'LSTAT']].boxplot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Два признака\n", "\n", "**Scatter Matrix** - скаттеры для каждой пары признаков\n", "\n", "На диагонали матрицы стоит гистограмма или kde (параметр *diagonal*). " ] }, { "cell_type": "code", "execution_count": 520, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from sklearn import datasets" ] }, { "cell_type": "code", "execution_count": 57, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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t3w733gvHjl18eIVwcaKgROuora1l9epNbNp0BJvNSb9+3bnpprGkpKQAUFxc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Zp6snplIRDs3LwT3RAd5m5mHA4HIX+IhKwE9EP1PP63x1HyFJKzk/F5fBw+cBjzSDP6fD3W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EjBkjKC9vOwWjouIYkycnodH0hTXT+oZhw4ahUp3BZjO12q4oMnZ7FhMmjPRQZIIgCIIg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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from pandas.tools.plotting import scatter_matrix\n", "\n", "iris = datasets.load_iris()\n", "data = pd.DataFrame(iris['data'], columns=iris['feature_names'])\n", "c = [\"red\", \"green\", \"blue\"]\n", "colors = [c[i] for i in iris['target']]\n", "_ = scatter_matrix(data, figsize=(16, 16), diagonal='kde', s=200, c=colors)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Дискретные признаки\n", "\n", "Для начала просто дискретизуем признаки. " ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "collapsed": false }, "outputs": [], "source": [ "f = (iris.data[:,3] - min(iris.data[:,3]))*4\n", "feature = np.zeros(len(f))\n", "feature[f > 1.5] = 1\n", "feature[f > 2] = 2\n", "feature[f > 6] = 3" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Теперь изобразим их просто скаттером." ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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xzmFZ57Csc771/YH9E1X1FEBVPQn8xDLtCvhCkjuTvLtnn5KkGXvJNYckXwDWTT/E5If9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\nSQ3DQZLUMBwkSY3/D7AvUUjUkdPcAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.scatter(np.zeros(feature.shape[0]), feature)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Кажется для дискретных признаков эта визуализация не очень информативна. Поэтому используем уже знакомый нам подход – сделаем jitter." ] }, { "cell_type": "code", "execution_count": 65, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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CrDXs2raL8vJyNO13z9vhcJiTTSc51nKMQMhPmjOdnRt3kpmZySM/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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(12, 7))\n", "plt.scatter(np.random.randn(len(feature)), feature, alpha=0.5, c=iris.target, s=100)\n", "plt.grid(True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Sklearn\n", "\n", "Библиотека с готовой реализацией алгоритмов машинного обучения ([sklearn](http://scikit-learn.org/stable/))." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Модель линейной регрессии. \n", "\n", "Обучающая выборка: $x_i$ — объект ($\\mathbb{R}^k$), $y_i$ — ответ ($\\mathbb{R}$)\n", "\n", "$X^l = \\{(x_i, y_i)\\}_{i=1}^l$\n", "\n", "Пытаемся восстановить неизвестную зависимость $a(x) = f(x, w)$, где $w \\in \\mathbb{R}^p$ — параметры, $f$ — выбранное семейство функций. \n", "\n", "Предполагаем, что $y(x) \\approx a(x)$\n", "\n", "Задача сводится к нахождению $w$.\n", "\n", "\n", "### Метод наименьших квадратов\n", "\n", "$Q(w, X) = \\sum_{i=1}^l(f(x_i; w) - y_i)^2 \\to \\min_{w}$\n", "\n", "### Линейная регрессия\n", "\n", "$f(x; w) = \\sum_{i=1}^n w_i * x_i + w_0 = \\langle w, x\\rangle$ (добавляем константный признак к данным)\n", "\n", "В двумерном пространстве соответствует прямой на плоскости.\n", "\n", "### Аналитическое решение\n", "\n", "$w = (X^TX)^{-1}X^Ty$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Для начала разделим все данные на обучающие и тестовые." ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from sklearn.cross_validation import train_test_split" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "collapsed": false }, "outputs": [], "source": [ "X_train, X_test, y_train, y_test = train_test_split(boston.data, boston.target, \n", " random_state=241, test_size=0.2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Обучим модель линейной регрессии:" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from sklearn.linear_model import LinearRegression" ] }, { "cell_type": "code", "execution_count": 66, "metadata": { "collapsed": true }, "outputs": [], "source": [ "?LinearRegression" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "У всех алгоритмов машинного обучения в библиотеке sklearn похожий интерфейс: \n", " - для начала нужно создать классификатор (и задать параметры, если требуется)\n", " - обучить модель необходимо вызвать метод fit, передав на вход матрицу с признаками и столбец ответов\n", " - для применения модели необходимо вызвать метод predict " ] }, { "cell_type": "code", "execution_count": 528, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=1, normalize=False)" ] }, "execution_count": 528, "metadata": {}, "output_type": "execute_result" } ], "source": [ "lr = LinearRegression()\n", "lr.fit(X_train, y_train)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Как мерить качество? \n", "\n", "Например, с помощью $MSE = \\dfrac{1}{l}\\sum_{i=1}^l{(a(x_i) - y_i)^2}$ или $MAE = \\dfrac{1}{l}\\sum_{i=1}^l{|a(x_i) - y_i|}$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Эти метрики уже реализованы в sklearn в модуле metrics:" ] }, { "cell_type": "code", "execution_count": 86, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from sklearn.metrics import mean_squared_error, mean_absolute_error" ] }, { "cell_type": "code", "execution_count": 530, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "3.39" ] }, "execution_count": 530, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mean_absolute_error(y_test, lr.predict(X_test))" ] }, { "cell_type": "code", "execution_count": 531, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "27.37" ] }, "execution_count": 531, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mean_squared_error(y_test, lr.predict(X_test))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Как понять: 27 — это много или мало?\n", "\n", "Можно ввести \"нормированный\" MSE — коэффициент детерминации:\n", "\n", "$R^2 = 1 - \\dfrac{\\sum_{i=1}^l{(a(x_i) - y_i)^2}}{\\sum_{i=1}^l{(y_i - \\bar{y})^2}}$, где $\\bar{y} = \\dfrac{1}{l}\\sum_{i=1}^l y_i$\n", "\n", "Его уже можно интерпретировать:\n", "- $R^2 \\approx 1$ — отлично\n", "- $R^2 \\approx 0$ — плохо\n", "- $R^2 < 0$ — ужасно" ] }, { "cell_type": "code", "execution_count": 88, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from sklearn.metrics import r2_score" ] }, { "cell_type": "code", "execution_count": 533, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "0.66" ] }, "execution_count": 533, "metadata": {}, "output_type": "execute_result" } ], "source": [ "r2_score(y_test, lr.predict(X_test))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "В чем недостаток тукущего способа оценки качества? Если немного поменять разбиение выборки на обучающую/тестовую, то качество может сильно измениться!" ] }, { "cell_type": "code", "execution_count": 534, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "3.64186894464\n", "24.3636130537\n", "0.731266198822\n" ] } ], "source": [ "X_train, X_test, y_train, y_test = train_test_split(boston.data, boston.target, random_state=13, test_size=0.2)\n", "\n", "lr = LinearRegression()\n", "lr.fit(X_train, y_train)\n", "\n", "print mean_absolute_error(y_test, lr.predict(X_test))\n", "print mean_squared_error(y_test, lr.predict(X_test))\n", "print r2_score(y_test, lr.predict(X_test))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Что делать в этом случае? Можно несколько раз разбить выборку на обучающую/тестовую, и итоговым качеством алгоритма считать среднее качество. Этот подходи называетс *K-fold*.\n", "\n", "![](http://scott.fortmann-roe.com/docs/docs/MeasuringError/crossvalidation.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Kfold также реализован в sklearn. Его обязательный параметр: размер выборки. Дальше вы можете по желанию указать количество фолдов (*n_folds*), и перемешивать ли данные (*shuffle*). В результате этот объект возвращает заданное количество (*n_folds*) количество пар индексов: для обучающей и тестовой выборки." ] }, { "cell_type": "code", "execution_count": 81, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from sklearn.cross_validation import KFold" ] }, { "cell_type": "code", "execution_count": 82, "metadata": { "collapsed": false }, "outputs": [], "source": [ "kFold = KFold(boston.target.shape[0], n_folds=5, shuffle=True, random_state=42)" ] }, { "cell_type": "code", "execution_count": 83, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def get_quality(regressor, X, y, kFold):\n", " metrics = {'mae': [], 'mse': [], 'r2': []}\n", " for train, test in kFold:\n", " regressor.fit(X[train], y[train])\n", " predict = regressor.predict(X[test])\n", " metrics['mae'].append(mean_absolute_error(y[test], predict))\n", " metrics['mse'].append(mean_squared_error(y[test], predict))\n", " metrics['r2'].append(r2_score(y[test], predict))\n", " return metrics" ] }, { "cell_type": "code", "execution_count": 538, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "mse 23.4932551603 1.84246315657\n", "mae 3.39074777444 0.183852969097\n", "r2 0.715147097604 0.037602797767\n" ] } ], "source": [ "for metric, scores in get_quality(LinearRegression(), boston.data, boston.target, kFold).iteritems():\n", " print metric, np.mean(scores), np.std(scores)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Чтобы можно было проинтерпретировать веса линейной модели, необходимо масштабировать данные. Например модифицируем данные таким образом, что:\n", " - среднее равно 0\n", " - среднеквадратичное отклонение равно 1" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from sklearn.preprocessing import StandardScaler" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "collapsed": false }, "outputs": [], "source": [ "scaler = StandardScaler()\n", "scaler.fit(boston.data)\n", "scaled_data = scaler.transform(boston.data)" ] }, { "cell_type": "code", "execution_count": 67, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([[-0.41771335, 0.28482986, -1.2879095 , ..., -1.45900038,\n", " 0.44105193, -1.0755623 ],\n", " [-0.41526932, -0.48772236, -0.59338101, ..., -0.30309415,\n", " 0.44105193, -0.49243937],\n", " [-0.41527165, -0.48772236, -0.59338101, ..., -0.30309415,\n", " 0.39642699, -1.2087274 ],\n", " ..., \n", " [-0.41137448, -0.48772236, 0.11573841, ..., 1.17646583,\n", " 0.44105193, -0.98304761],\n", " [-0.40568883, -0.48772236, 0.11573841, ..., 1.17646583,\n", " 0.4032249 , -0.86530163],\n", " [-0.41292893, -0.48772236, 0.11573841, ..., 1.17646583,\n", " 0.44105193, -0.66905833]])" ] }, "execution_count": 67, "metadata": {}, "output_type": "execute_result" } ], "source": [ "scaled_data" ] }, { "cell_type": "code", "execution_count": 68, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([ 6.34099712e-17, -6.34319123e-16, -2.68291099e-15,\n", " 4.70199198e-16, 2.49032240e-15, -1.14523016e-14,\n", " -1.40785495e-15, 9.21090169e-16, 5.44140929e-16,\n", " -8.86861950e-16, -9.20563581e-15, 8.16310129e-15,\n", " -3.37016317e-16])" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.mean(scaled_data, axis=0)" ] }, { "cell_type": "code", "execution_count": 41, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "LSTAT -3.74867981912\n", "DIS -3.10444805148\n", "RM 2.67064141332\n", "RAD 2.65878654091\n", "TAX -2.07589814093\n", "PTRATIO -2.06215592597\n", "NOX -2.06009246354\n", "ZN 1.08098057817\n", "CRIM -0.9204111277\n", "B 0.856640435817\n", "CHAS 0.682203460284\n", "INDUS 0.14296712402\n", "AGE 0.0211206306213\n" ] } ], "source": [ "lr = LinearRegression().fit(scaled_data, boston.target)\n", "for feature, coef in sorted(zip(boston.feature_names, lr.coef_), key=lambda x: abs(x[1]), reverse=True):\n", " print feature, coef" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Иногда после обучения линейной модели получаются слишком большие веса. Обычно это свидетельствует о переобучении. Поэтому в модель вводят регуляризацию, то есть штраф на слишком большие значения весов.\n", "\n", "### Ridge regression\n", "\n", "Например, так называемый $L_2$ регуляризатор — квадрат $L_2$ нормы вектора весов:\n", "\n", "$\\left\\lVert w \\right\\rVert_2^2 = \\sum_{j=1}^p w^2$\n", "\n", "Теперь задача будет иметь следующий вид:\n", "\n", "$Q(w, X) = \\sum_{i=1}^l(f(x_i; w) - y_i)^2 + \\alpha_2 \\left\\lVert w \\right\\rVert_2^2 \\to \\min_{w}$" ] }, { "cell_type": "code", "execution_count": 541, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from sklearn.linear_model import Ridge" ] }, { "cell_type": "code", "execution_count": 542, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "mse 23.5647341986 1.95053677092\n", "mae 3.35621197703 0.201701366897\n", "r2 0.714360180038 0.0377762819421\n" ] } ], "source": [ "for metric, scores in get_quality(Ridge(alpha=10), scaled_data, boston.target, kFold).iteritems():\n", " print metric, np.mean(scores), np.std(scores)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Остался вопрос как подбирать $\\alpha$? И что это вообще такое?\n", "\n", "В алгоритмах машинного обучения следует различать параметры модели и гиперпараметры (структурные параметры). Обычно параметры модели настраиваются в ходе обучения (например, веса в линейной модели), в то время как гиперпараметры задаются заранее (например, $\\alpha$ в регуляризованной линейной модели). Каждая модель обычно имеет множество гиперпараметров, и нет универсальных наборов гиперпараметров, оптимально работающих во всех задачах, для каждой задачи нужно подбирать свой набор.\n", "\n", "Для оптимизации гиперпараметров модели часто используют перебор по сетке (grid search): для каждого гиперпараметра выбирается несколько значений, перебираются все комбинации значений и выбирается комбинация, на которой модель показывает лучшее качество (с точки зрения метрики, которая оптимизируется). Однако в этом случае нужно грамотно оценивать построенную модель, а именно делать разбиение на обучающую и тестовую выборку. Есть несколько схем, как это можно реализовать:\n", "\n", " - Разбить имеющуюся выборку на обучающую и тестовую. В этом случае сравнение большого числа моделей при переборе параметров приводит к ситуации, когда лучшая на тестовой подвыборке модель не сохраняет свои качества на новых данных. Можно сказать, что происходит переобучение на тестовую выборку.\n", " - Для устранения описанной выше проблемы, можно разбить данные на 3 непересекающихся подвыборки: обучение (train), валидация (validation) и контроль (test). Валидационную подвыборку используют для сравнения моделей, а test — для окончательной оценки качества и сравнения семейств моделей с подобранными параметрами.\n", " - Другой способ сравнения моделей — кросс-валидация. Существуют различные схемы кросс-валидации:\n", " - Leave-One-Out (убираем из выборки один объект, обучаемся на оставшейся, предсказываем качество на убранном объекте)\n", " - K-Fold\n", " - Многократное случайное разбиение выборки" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Для Ridge-регрессии реализован специальный класс, позволяющий подобрать оптимальное $\\alpha$." ] }, { "cell_type": "code", "execution_count": 543, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from sklearn.linear_model import RidgeCV" ] }, { "cell_type": "code", "execution_count": 544, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "1.00" ] }, "execution_count": 544, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rcv = RidgeCV(alphas=(0.01, 0.1, 1.0), cv=kFold)\n", "rcv.fit(scaled_data, boston.target)\n", "rcv.alpha_" ] }, { "cell_type": "code", "execution_count": 545, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "mse 23.4927932848 1.85542596288\n", "mae 3.3855230191 0.185203170524\n", "r2 0.715158625182 0.0376359203817\n" ] } ], "source": [ "for metric, scores in get_quality(Ridge(alpha=1.0), scaled_data, boston.target, kFold).iteritems():\n", " print metric, np.mean(scores), np.std(scores)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Lasso regression\n", "\n", "\n", "$\\left\\lVert w \\right\\rVert_1 = \\sum_{j=1}^p |w|$\n", "\n", "Теперь задача будет иметь следующий вид:\n", "\n", "$Q(w, X) = \\sum_{i=1}^l(f(x_i; w) - y_i)^2 + \\alpha_1 \\left\\lVert w \\right\\rVert_1 \\to \\min_{w}$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Качество в данном случае получилось немного меньше, в чем дело? После введения регуляризатора модель становится чувствительной к масштабу." ] }, { "cell_type": "code", "execution_count": 78, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from sklearn.linear_model import Lasso, LassoCV" ] }, { "cell_type": "code", "execution_count": 84, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "0.01" ] }, "execution_count": 84, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rcv = LassoCV(alphas=(0.001, 0.01, 0.1, 1.0, 10.0), cv=kFold)\n", "rcv.fit(scaled_data, boston.target)\n", "rcv.alpha_" ] }, { "cell_type": "code", "execution_count": 89, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "mse 23.4845738831 1.86459144401\n", "mae 3.38158579565 0.186140273659\n", "r2 0.715250581386 0.0377123576456\n" ] } ], "source": [ "for metric, scores in get_quality(Lasso(alpha=0.01), scaled_data, boston.target, kFold).iteritems():\n", " print metric, np.mean(scores), np.std(scores)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Особенность $L_1$ регуляризатора в том, что он \"отбирает признаки\": зануляет коэффициенты перед некоторыми \"неважными\" признаками. Например:" ] }, { "cell_type": "code", "execution_count": 549, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([-0.89, 1.04, 0.05, 0.68, -1.98, 2.68, 0. , -3.06, 2.48,\n", " -1.9 , -2.04, 0.85, -3.74])" ] }, "execution_count": 549, "metadata": {}, "output_type": "execute_result" } ], "source": [ "lasso = Lasso(alpha=0.01).fit(scaled_data, boston.target)\n", "lasso.coef_" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### ElasticNet\n", "\n", "\n", "$Q(w, X) = \\sum_{i=1}^l(f(x_i; w) - y_i)^2 + \\alpha_1 \\left\\lVert w \\right\\rVert_1 + \\alpha_2 \\left\\lVert w \\right\\rVert_2^2\\to \\min_{w}$" ] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.10" } }, "nbformat": 4, "nbformat_minor": 0 }