{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Необычные модели Playboy, или про обнаружение выбросов в данных c помощью Scikit-learn\n",
    "#### Автор материала: преподаватель Факультета Компьютерных Наук НИУ ВШЭ Кашницкий Юрий"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Загрузка и первичный анализ данных"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "from __future__ import division, print_function\n",
    "# отключим всякие предупреждения Anaconda\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "%pylab inline\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "from sklearn.preprocessing import scale\n",
    "from sklearn import svm\n",
    "from scipy import stats\n",
    "from sklearn.decomposition import PCA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Считываем данные по моделям Playboy.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "girls = pd.read_csv('data/girls.csv', header=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Процент \"выбросов\", задаваемый пользователем. Ищем 1% выбросов в данных, то есть ограничимся 6-7 «странными» девушками. (Переменные в Python, записанные в верхнем регистре, символизируют константы и обычно записываются в начале файла после подключения модулей).**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "OUTLIER_FRACTION = 0.01"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Посмотрим общую статистику девушек.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 604 entries, 0 to 603\n",
      "Data columns (total 7 columns):\n",
      "Month     604 non-null object\n",
      "Year      604 non-null int64\n",
      "Bust      604 non-null int64\n",
      "Waist     604 non-null int64\n",
      "Hips      604 non-null int64\n",
      "Height    604 non-null int64\n",
      "Weight    604 non-null int64\n",
      "dtypes: int64(6), object(1)\n",
      "memory usage: 37.8+ KB\n"
     ]
    }
   ],
   "source": [
    "girls.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Дальше узнаем про девушек побольше.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Bust</th>\n",
       "      <th>Waist</th>\n",
       "      <th>Hips</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>604.000000</td>\n",
       "      <td>604.000000</td>\n",
       "      <td>604.000000</td>\n",
       "      <td>604.000000</td>\n",
       "      <td>604.000000</td>\n",
       "      <td>604.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1983.057947</td>\n",
       "      <td>89.293046</td>\n",
       "      <td>59.529801</td>\n",
       "      <td>87.942053</td>\n",
       "      <td>167.887417</td>\n",
       "      <td>52.168874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>14.843740</td>\n",
       "      <td>3.994011</td>\n",
       "      <td>3.616909</td>\n",
       "      <td>3.479142</td>\n",
       "      <td>5.776711</td>\n",
       "      <td>4.040585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1953.000000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>46.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>42.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1970.000000</td>\n",
       "      <td>86.000000</td>\n",
       "      <td>58.000000</td>\n",
       "      <td>86.000000</td>\n",
       "      <td>165.000000</td>\n",
       "      <td>49.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1983.000000</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>168.000000</td>\n",
       "      <td>52.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1996.000000</td>\n",
       "      <td>91.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>91.000000</td>\n",
       "      <td>173.000000</td>\n",
       "      <td>54.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2009.000000</td>\n",
       "      <td>104.000000</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>188.000000</td>\n",
       "      <td>68.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Year        Bust       Waist        Hips      Height      Weight\n",
       "count   604.000000  604.000000  604.000000  604.000000  604.000000  604.000000\n",
       "mean   1983.057947   89.293046   59.529801   87.942053  167.887417   52.168874\n",
       "std      14.843740    3.994011    3.616909    3.479142    5.776711    4.040585\n",
       "min    1953.000000   81.000000   46.000000   61.000000  150.000000   42.000000\n",
       "25%    1970.000000   86.000000   58.000000   86.000000  165.000000   49.000000\n",
       "50%    1983.000000   89.000000   61.000000   89.000000  168.000000   52.000000\n",
       "75%    1996.000000   91.000000   61.000000   91.000000  173.000000   54.000000\n",
       "max    2009.000000  104.000000   89.000000   99.000000  188.000000   68.000000"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "girls.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Посмотрим на выбросы, которые бросаются в глаза.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Month</th>\n",
       "      <th>Year</th>\n",
       "      <th>Bust</th>\n",
       "      <th>Waist</th>\n",
       "      <th>Hips</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>483</th>\n",
       "      <td>December</td>\n",
       "      <td>1998</td>\n",
       "      <td>86</td>\n",
       "      <td>89</td>\n",
       "      <td>86</td>\n",
       "      <td>173</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Month  Year  Bust  Waist  Hips  Height  Weight\n",
       "483  December  1998    86     89    86     173      52"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "girls[girls['Waist'] == 89]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Для красоты можно еще построить и гистограммы распределения параметров девушек.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Распределение охвата груди.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10e078e90>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAesAAAFVCAYAAADPM8ekAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n1gAAGEesAQAwjlgDAGAcsQYAwLj/Bwm2HK02nsEdAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e078bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "girls['Bust'].hist(bins=40, facecolor='blue', label=\"Bust\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Распределение охвата талии.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x110b4bdd0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAegAAAFVCAYAAAAkBHynAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nEWgAAAwi0AAAGPR/GZw6MKUWFzsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e6efad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "girls['Waist'].hist(bins=40, label=\"Waist\", facecolor='red')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Распределение охвата бедер.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1114c5810>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAesAAAFVCAYAAADPM8ekAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAFahJREFUeJzt3W9s1fX99/FXoWUbLR2a4Z3JKmmIARUStEbcRG8IsoVk\n2+W4DEwwyiKwaVxwiUxFUEY0ccZkw2XOuCzBOWCZy7Yby6JGxiJuzC0iiOKGPxm6RVnAre2UU9dz\n3dg1foLQP9jST08fj1u2/fr9ft79tH3S0/Z76qrVajUAQLFGDfUCAICeiTUAFE6sAaBwYg0AhRNr\nACicWANA4ep7emNXV1duvfXW/PWvf02lUsny5cvT2tqalStXZtSoUZk8eXJWr16durq6bN68OZs2\nbUp9fX2WL1+eyy677BSNAAC1rcdY/+IXv8jpp5+ee++9N//4xz/y2c9+NlOmTMmKFSvS1taW1atX\n58knn8z06dOzYcOGPPbYYzl8+HAWLFiQiy++OGPGjDlVcwBAzeox1nPnzs0VV1yRJOnu7k59fX12\n796dtra2JMmsWbPy9NNPZ9SoUZkxY0YaGhrS0NCQlpaW7NmzJ+edd97gTwAANa7Hn1mPHTs2jY2N\n6ejoyE033ZSvfvWr6e7uPvL2xsbGtLe3p6OjI+PGjTvq9R0dHYO3agAYQXr9BbO//e1vueaaa/K5\nz30u8+bNy6hR//u/dHR0pLm5OU1NTens7Dzy+s7OzjQ3N/d4Xnc5BYC+6fFh8L///e+57rrrsnr1\n6lx00UVJkilTpmT79u258MILs3Xr1sycOTPTpk3L/fffn0qlksOHD2fv3r2ZPHlyjxeuq6vLgQPt\nAzdJYSZMGGe+YayW56vl2RLzDXcjYb6T0WOsv/vd76a9vT0PPPBAHnjggSTJbbfdlnXr1qWrqyut\nra2ZO3du6urqsnjx4ixcuDDd3d1ZsWKFXy4DgAFSN5TPulXr/3oy3/BVy/PV8myJ+Ya7kTDfyXBT\nFAAonFgDQOHEGgAKJ9YAUDixBoDCiTUAFE6sAaBwYg0AhRNrACicWANA4Xq8NzhALalUKtm/f1+f\nj584scXzHFAEsQZGjP3792XmA+cn4/tw8FvJM1/5Q1pbe34GQTgVxBoYWcYn+dhQLwL6x8+sAaBw\nYg0AhRNrACicWANA4cQaAAon1gBQOLEGgMKJNQAUTqwBoHBiDQCFE2sAKJxYA0DhxBoACifWAFA4\nsQaAwok1ABROrAGgcGINAIUTawAonFgDQOHEGgAKJ9YAUDixBoDCiTUAFE6sAaBwYg0AhRNrACic\nWANA4cQaAAon1gBQOLEGgMKJNQAUTqwBoHBiDQCFE2sAKJxYA0DhxBoACifWAFA4sQaAwok1ABSu\nfqgXADBSVCqV7N+/r0/HTpzYkjFjxgzyihguxBrgFNm/f19mPnB+Mr6XA99KnvnKH9LaOvmUrIvy\niTXAqTQ+yceGehEMN35mDQCFE2sAKJxYA0DhxBoACifWAFA4sQaAwok1ABROrAGgcGINAIUTawAo\nnFgDQOHEGgAKJ9YAULg+xXrHjh1ZtGhRkmT37t2ZNWtWFi1alEWLFuWXv/xlkmTz5s258sorc9VV\nV2XLli2DtmAAGGl6fYrMhx56KD//+c/T2NiYJHnhhRdy7bXX5tprrz1yzIEDB7Jhw4Y89thjOXz4\ncBYsWJCLL77YE6cDwADo9TvrlpaWrF+/PtVqNUmya9eubNmyJVdffXVuu+22dHZ25vnnn8+MGTPS\n0NCQpqamtLS0ZM+ePYO+eAAYCXqN9Zw5czJ69OgjL0+fPj233HJLHnnkkUycODHr169PZ2dnxo0b\nd+SYxsbGdHR0DM6KAWCE6fVh8GPNnj37SJhnz56dtWvXpq2tLZ2dnUeO6ezsTHNzc6/nmjBhXK/H\nDGfmG95qeb5ani058XyHDjX16zynn940oO+r/ly/p2uP1P0byfod6yVLluT222/PtGnTsm3btpx7\n7rmZNm1a7r///lQqlRw+fDh79+7N5MmTez3XgQPtJ7Xo4WDChHHmG8Zqeb5ani3peb6DB/v3iN/B\ngx0D+r7qz/VPdO2RvH+14GT/IdLnWNfV1SVJ1qxZk7Vr16a+vj5nnHFG7rrrrjQ2Nmbx4sVZuHBh\nuru7s2LFCr9cBgADpE+xPvPMM7Nx48YkydSpU/OjH/3ofcfMnz8/8+fPH9jVAQBuigIApRNrACic\nWANA4cQaAAon1gBQOLEGgMKJNQAUTqwBoHBiDQCFE2sAKFy/n8gDgHJUKpXs37+vz8dPnNjiuRuG\nIbEGGMb279+XmQ+cn4zvw8FvJc985Q9pbe39WREpi1gDDHfjk3xsqBfBYPIzawAonFgDQOHEGgAK\nJ9YAUDixBoDCiTUAFE6sAaBwYg0AhRNrACicWANA4cQaAAon1gBQOLEGgMKJNQAUTqwBoHBiDQCF\nE2sAKJxYA0DhxBoACifWAFA4sQaAwok1ABROrAGgcGINAIUTawAonFgDQOHEGgAKJ9YAUDixBoDC\niTUAFE6sAaBwYg0AhRNrACicWANA4cQaAAon1gBQOLEGgMKJNQAUTqwBoHBiDQCFE2sAKJxYA0Dh\nxBoACifWAFA4sQaAwok1ABROrAGgcGINAIUTawAonFgDQOHEGgAKJ9YAUDixBoDCiTUAFE6sAaBw\nYg0AhetTrHfs2JFFixYlSfbt25cFCxbki1/8YtasWZNqtZok2bx5c6688spcddVV2bJly6AtGABG\nml5j/dBDD+X2229PV1dXkuTuu+/OihUr8sMf/jDVajVPPvlkDhw4kA0bNmTjxo15+OGHc99996VS\nqQz64gFgJOg11i0tLVm/fv2R76B3796dtra2JMmsWbOybdu27Ny5MzNmzEhDQ0OamprS0tKSPXv2\nDO7KAWCEqO/tgDlz5uS111478vJ/o50kjY2NaW9vT0dHR8aNG3fU6zs6Onq9+IQJ43o9Zjgz3/BW\ny/PV8mzJiec7dKipX+c5/fSmAX1f9ef6PV37va8f6pkGQ+nrGwq9xvpYo0b97zfjHR0daW5uTlNT\nUzo7O4+8vrOzM83Nzb2e68CB9v5eftiYMGGc+YaxWp6vlmdLep7v4MHev4k49viBfF/15/onuvax\n8w31TANtJHx8nox+/zb4lClTsn379iTJ1q1bc8EFF2TatGl59tlnU6lU0t7enr1792by5MkntSAA\n4Gh9/s66rq4uSbJy5cqsWrUqXV1daW1tzdy5c1NXV5fFixdn4cKF6e7uzooVKzJmzJhBWzQAjCR9\nivWZZ56ZjRs3JknOOuusbNiw4X3HzJ8/P/Pnzx/Y1QEAbooCAKUTawAonFgDQOHEGgAKJ9YAUDix\nBoDCiTUAFE6sAaBwYg0AhRNrACicWANA4cQaAAon1gBQOLEGgMKJNQAUTqwBoHBiDQCFE2sAKJxY\nA0DhxBoACifWAFA4sQaAwok1ABROrAGgcGINAIUTawAonFgDQOHEGgAKJ9YAUDixBoDCiTUAFE6s\nAaBwYg0AhRNrACicWANA4cQaAAon1gBQOLEGgMKJNQAUTqwBoHBiDQCFE2sAKJxYA0DhxBoACifW\nAFA4sQaAwok1ABROrAGgcGINAIUTawAonFgDQOHEGgAKJ9YAUDixBoDCiTUAFE6sAaBwYg0AhRNr\nACicWANA4cQaAAon1gBQOLEGgMKJNQAUTqwBoHBiDQCFE2sAKJxYA0DhxBoACld/sv/j5z//+TQ1\nNSVJJk6cmKVLl2blypUZNWpUJk+enNWrV6eurm7AFgoAI9VJxfrw4cNJkg0bNhx53bJly7JixYq0\ntbVl9erVefLJJ3P55ZcPzCoBYAQ7qYfBX3rppbz99ttZsmRJrrnmmjz33HPZvXt32trakiSzZs3K\ntm3bBnShADBSndR31h/5yEeyZMmSzJ8/P6+++mq+9KUvHfX2sWPHpr29fUAWCAAj3UnF+qyzzkpL\nS8uR/x4/fnxefPHFI2/v7OxMc3Nzr+eZMGHcyVx+2DDf8FbL89XybMmJ5zt0qKlf5zn99KYBfV/1\n5/o9Xfu9rx/qmQZD6esbCicV65/85Cd5+eWXs3r16rzxxhvp7OzMJz/5yWzfvj0XXnhhtm7dmpkz\nZ/Z6ngMHave77wkTxplvGKvl+Wp5tqTn+Q4e7OjXuQ4e7BjQ91V/rn+iax8731DPNNBGwsfnyTip\nWH/hC1/IypUrs3DhwtTV1eXuu+/O+PHjs2rVqnR1daW1tTVz5849qQUBAEc7qVg3NDTkvvvue9/r\n3/vb4QDAwHBTFAAonFgDQOHEGgAKJ9YAUDixBoDCiTUAFE6sAaBwYg0AhRNrACicWANA4cQaAAon\n1gBQOLEGgMKJNQAUTqwBoHBiDQCFE2sAKJxYA0DhxBoACifWAFA4sQaAwtUP9QIAjqdSqWT//n19\nOnbixJaMGTNmkFcEQ0esgSLt378vMx84Pxnfy4FvJc985Q9pbZ18StYFQ0GsgXKNT/KxoV4EDD0/\nswaAwok1ABROrAGgcGINAIUTawAonFgDQOH86RZwXP25KUnixiQwmMQaOK4+35QkcWMSGGRiDZyY\nm5JAEfzMGgAKJ9YAUDixBoDCiTUAFE6sAaBwYg0AhRNrACicWANA4cQaAAon1gBQOLEGgMKJNQAU\nTqwBoHCedQuAk9af5z33nOcnT6wBOGl9ft5zz3n+gYg1AB+M5z0fdH5mDQCFE2sAKJxYA0DhxBoA\nCifWAFA4sQaAwok1ABROrAGgcGINAIUTawAonFgDQOHEGgAKJ9YAUDixBoDCeYpMYHj7d/KXv+w7\n8uKhQ005eLDjuIe+97iBUqlUsn9/387b5+v/+8THHjvfYMxEecQaGN7+mVz1i//zn+dU7s1fknxi\nYC+/f/++zHzg/IG9/hDPRHnEGhj+xif5WB+OOzSMrj/UM1EUsQbgKIPy0P4g6c9aJ05syZgxYwZ5\nRYNDrAE4yqA8tD9I+rzWt5JnvvKHtLZOPiXrGmhiDcD7DaeH4fu61mFsQGPd3d2dNWvW5OWXX05D\nQ0PWrVuXT3zCbz4AMHyU+ND6gMb6iSeeSFdXVzZu3JgdO3bknnvuyXe+852BvERN6M8HQjLwHwxD\nff3hYqjfT4Nx/UqlkpdffvmEf9r0XkP9s0hqTA9/jvZe//3TtKH8ulPiQ+sDGus//vGPueSSS5Ik\n06dPz65duwbkvFev/r95rf61Xo+rHurOj1f+PGecccaAXHew9OvnQYPwwTDU1x8uhvr9NBjXH04/\ni6TG9OfP0Ur4ulPYQ+sDGuuOjo40NTUdeXn06NHp7u7OqFEf7EZp71Teyb+qnb0f2JX8z/+8kvb2\nf3yg6w2Egbwxw0B/hzMQ1+9pvlpw6FBTTezTBz1n3ur7cYMyf1+u356kro8n7c+xfZypz+vsz/Vr\ndabmPp4zff946vNa+/Ex2p9znip11Wq1OlAnu+eeezJ9+vR8+tOfTpJceuml+fWvfz1QpweAEWlA\n7w0+Y8aMbN26NUny3HPP5eyzzx7I0wPAiDSg31lXq9WsWbMme/bsSZLcfffdmTRp0kCdHgBGpAGN\nNQAw8DxFJgAUTqwBoHBiDQCFE2sAKNwpeyKPBx98ME899VQqlUoWLlyYtra2rFy5MqNGjcrkyZOz\nevXq1NX19S/7y3PsfFOnTs3SpUtz1llnJUkWLFiQz3zmM0O7yJP005/+NI899liS5PDhw3nppZfy\n6KOPZt26dcN+/44326ZNm3L99dfXxN51dXVl5cqVef311zN69OisXbs2o0ePrpnPvePN984779TM\n516lUsnXv/71vPbaa2lqasodd9yRJDWzf8ebr7Ozc9jv344dO/LNb34zGzZsyL59+467X5s3b86m\nTZtSX1+f5cuX57LLLuv5pNVT4Le//W116dKl1Wq1Wu3s7Kx++9vfri5btqy6ffv2arVard5xxx3V\nxx9//FQsZVAcb77NmzdXv//97w/xygbenXfeWd28eXNN7d9//Xe2Wtq7xx9/vHrTTTdVq9Vq9emn\nn67ecMMNNbV3x85344031tT+bdiwobpq1apqtVqtvvLKK9XrrruupvbvePMN9/373ve+V503b171\nqquuqlar1erSpUvft19vvvlmdd68edVKpVJtb2+vzps3r3r48OEez3tKHgZ/+umnc/bZZ+fLX/5y\nli1blssuuywvvPBC2trakiSzZs3Ktm3bTsVSBsWJ5tuyZUuuvvrq3Hbbbens7MPtUgu3c+fO/PnP\nf878+fNrav+S/8z2pz/9KfPnz8+uXbtqZu8mTZqUf//736lWq2lvb09DQ0NN7d2x89XX19fU597e\nvXsza9asJP+Zde/evdm9e3fN7N+x873yyivDfv9aWlqyfv36VP//X0Ufb7927tyZGTNmpKGhIU1N\nTWlpaTlyf5ITOSWxPnjwYHbt2pVvfetbufPOO3PzzTcfGSRJxo4dm/b29lOxlEFxvPmmT5+eW265\nJY888kgmTpyY9evXD/UyP7AHH3wwN9xwQ5LU1P4l/5ntxhtvTJKa2ruxY8fm9ddfz9y5c3PHHXdk\n0aJFNbV3x5tv2rRpNbN/U6ZMyVNPPZXkP3eFfPPNN9Pd3X3k7cN9/46d74033sh55503rPdvzpw5\nGT169JGX3/v51tjYmPb29nR0dGTcuHFHvb6jo+fnWjglsT7ttNPyqU99KvX19Zk0aVI+9KEPHbWw\nzs7ONDf34w7vhTl2vg9/+MO59NJLM3Xq1CTJ5ZdfnhdffHGIV/nB/POf/8yrr76aCy+8MEmOenKW\n4b5/x842e/bsmtm7H/zgB7nkkkvyq1/9Kj/72c9yyy235N133z3y9uG+d8fOt3LlysyaNatm9u/K\nK69MU1NTFi5cmCeeeCLnnHPOUSEY7vt3vPnmzJlTM/uXHP21sqOjI83NzWlqajrqEYO+7OMpifX5\n55+f3/zmN0mSN954I++8804uuuiibN++PUmydevWXHDBBadiKYPi2PnefvvtXH/99Xn++eeTJM88\n80zOPffcoVziB/b73/8+F1100ZGXp0yZUjP7d+xsS5YsqZm9++hHP5rGxsYkSXNzc959991MnTq1\nZvbu2Pm6urqybNmymtm/nTt3ZubMmXn00UdzxRVXZOLEiTX1uXe8+Wrp8y85/tfKadOm5dlnn02l\nUkl7e3v27t2byZN7fjrQU3a70XvvvTe/+93v0t3dnZtvvjkf//jHs2rVqnR1daW1tTXf+MY3hu1v\nNCbvn++0007L2rVrU19fnzPOOCN33XXXkS8qw9HDDz+choaGLF68OEny6quv1sz+HTvb7t27a2bv\n/vWvf+XWW2/NgQMH0tXVlWuuuSbnnHNOzezd8eabNGlSzezfoUOHsmLFirz99ttpbm7OunXr0tnZ\nWTP7d7z5Dhw4MOz377XXXsvXvva1bNy48YRfK3/84x9n06ZN6e7uzvLlyzN79uwez+ne4ABQODdF\nAYDCiTUAFE6sAaBwYg0AhRNrACicWANA4cQaAAr3/wD71Hn1B31nXwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1114cf990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "girls['Hips'].hist(bins=40, label=\"Hips\", facecolor='green')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Распределение роста.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11169c990>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeoAAAFVCAYAAAAg8ayaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/wFbRFL/1Vb33AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111748f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "girls['Height'].hist(bins=40, label=\"Height\", facecolor='cyan')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Распределение веса.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x111a8e590>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAegAAAFVCAYAAAAkBHynAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nBVpAh6YkWVYoAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111a96450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "girls['Weight'].hist(bins=40, label=\"Weight\", facecolor='yellow')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x11171a190>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA38AAAN9CAYAAAAjf8CEAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJ4QQQgghhBD1wP8AxEbQSnSsjS0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111dd6750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(girls[['Bust', 'Waist', 'Hips', 'Height', 'Weight']])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Предобработка данных"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Убираем признаки `месяц` и `год`.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "girl_params = np.array(girls.values[:,2:], dtype=\"float64\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Шкалируем данные.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "girl_params = scale(girl_params) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Выделяем в них две главные компоненты.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X = PCA(n_components=2).fit_transform(girl_params)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Обучение модели"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Для обнаружения «выбросов» в данных используем одноклассовую машину опорных векторов. \n",
    "Создаем SVM классификатор с гауссовым ядром.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "svm_clf = svm.OneClassSVM(kernel=\"rbf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**\"Скармливаем\" ему данные.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OneClassSVM(cache_size=200, coef0=0.0, degree=3, gamma='auto', kernel='rbf',\n",
       "      max_iter=-1, nu=0.5, random_state=None, shrinking=True, tol=0.001,\n",
       "      verbose=False)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "svm_clf.fit(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**В результате обучения алгоритма получаем вектор\n",
    "индикаторов, является ли объект \"выбросом\".**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Поиск выбросов"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "dist_to_border = svm_clf.decision_function(X).ravel()\n",
    "threshold = stats.scoreatpercentile(dist_to_border,\n",
    "            100 * OUTLIER_FRACTION)\n",
    "is_outlier = dist_to_border < threshold"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Отображение и трактовка результатов"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Визуализация.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-7, 7)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAd4AAAFeCAYAAAArLn4bAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114a7ab10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "girls_num = girl_params.shape[0]\n",
    "xx, yy = np.meshgrid(np.linspace(-7, 7, 500), np.linspace(-7, 7, 500))\n",
    "n_inliers = int((1. - OUTLIER_FRACTION) * girls_num)\n",
    "n_outliers = int(OUTLIER_FRACTION * girls_num)\n",
    "Z = svm_clf.decision_function(np.c_[xx.ravel(), yy.ravel()])\n",
    "Z = Z.reshape(xx.shape)\n",
    "plt.title(\"Outlier detection\")\n",
    "plt.contourf(xx, yy, Z, levels=np.linspace(Z.min(), threshold, 7),\n",
    "                         cmap=plt.cm.Blues_r)\n",
    "a = plt.contour(xx, yy, Z, levels=[threshold],\n",
    "                            linewidths=2, colors='red')\n",
    "plt.contourf(xx, yy, Z, levels=[threshold, Z.max()],\n",
    "                         colors='orange')\n",
    "b = plt.scatter(X[is_outlier, 0], X[is_outlier, 1], c='black')\n",
    "c = plt.scatter(X[is_outlier == 0, 0], X[is_outlier == 0, 1], c='white')\n",
    "plt.axis('tight')\n",
    "plt.legend([a.collections[0], b, c],\n",
    "           ['learned decision function', 'outliers', 'inliers'],\n",
    "           prop=matplotlib.font_manager.FontProperties(size=11))\n",
    "plt.xlim((-7, 7))\n",
    "plt.ylim((-7, 7))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Смотрим на \"выбросы\" - девушек с параметрами, отличающимися от средних.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Month</th>\n",
       "      <th>Year</th>\n",
       "      <th>Bust</th>\n",
       "      <th>Waist</th>\n",
       "      <th>Hips</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>September</td>\n",
       "      <td>1962</td>\n",
       "      <td>91</td>\n",
       "      <td>46</td>\n",
       "      <td>86</td>\n",
       "      <td>152</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>October</td>\n",
       "      <td>1963</td>\n",
       "      <td>94</td>\n",
       "      <td>66</td>\n",
       "      <td>94</td>\n",
       "      <td>183</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>October</td>\n",
       "      <td>1964</td>\n",
       "      <td>104</td>\n",
       "      <td>64</td>\n",
       "      <td>97</td>\n",
       "      <td>168</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>September</td>\n",
       "      <td>1972</td>\n",
       "      <td>98</td>\n",
       "      <td>64</td>\n",
       "      <td>99</td>\n",
       "      <td>185</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>483</th>\n",
       "      <td>December</td>\n",
       "      <td>1998</td>\n",
       "      <td>86</td>\n",
       "      <td>89</td>\n",
       "      <td>86</td>\n",
       "      <td>173</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>December</td>\n",
       "      <td>2000</td>\n",
       "      <td>86</td>\n",
       "      <td>66</td>\n",
       "      <td>91</td>\n",
       "      <td>188</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>535</th>\n",
       "      <td>April</td>\n",
       "      <td>2003</td>\n",
       "      <td>86</td>\n",
       "      <td>61</td>\n",
       "      <td>69</td>\n",
       "      <td>173</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Month  Year  Bust  Waist  Hips  Height  Weight\n",
       "54   September  1962    91     46    86     152      45\n",
       "67     October  1963    94     66    94     183      68\n",
       "79     October  1964   104     64    97     168      66\n",
       "173  September  1972    98     64    99     185      64\n",
       "483   December  1998    86     89    86     173      52\n",
       "507   December  2000    86     66    91     188      61\n",
       "535      April  2003    86     61    69     173      54"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "girls[is_outlier]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " - Мики Уинтерс. Сентябрь, 1962. 91-46-86, рост 152, вес 45. \n",
    " \n",
    "<img src=\"img/girl1.jpg\">\n",
    "\n",
    "- Кристин Уильямс. Октябрь, 1963. 94-66-94, рост 183, вес 68.\n",
    "\n",
    "<img src=\"img/girl2.jpg\">\n",
    "\n",
    "- Розмари Хилкрест. Октябрь, 1964. 104-64-97, рост 168, вес 66.\n",
    "\n",
    "<img src=\"img/girl3.jpg\">\n",
    "\n",
    "- Сюзан Миллер. Сентябрь, 1972. 98-64-99, рост 185, вес 64.\n",
    "\n",
    "<img src=\"img/girl4.jpg\">\n",
    "\n",
    "- Тройняшки Дам. 86-89 (реально 64)-86, рост 173, вес 52. \n",
    "\n",
    "<img src=\"img/girl5.jpg\">\n",
    "\n",
    "- Кара Мишель. Декабрь, 2000. 86-66-91, рост 188, вес 61.\n",
    "\n",
    "<img src=\"img/girl6.jpg\">\n",
    "\n",
    "- Кармелла де Сезаре. Апрель, 2003. 86-61-69, рост 173, вес 54. \n",
    "\n",
    "<img src=\"img/girl7.jpg\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ссылки\n",
    "- Материал этой тетрадки в <a href=\"http://habrahabr.ru/post/251225/\">статье</a> на Хабрахабре\n",
    "- <a href=\"http://scikit-learn.org/stable/auto_examples/covariance/plot_outlier_detection.html#example-covariance-plot-outlier-detection-py\">Пример</a> Sklearn на обнаружение выбросов в синтетических данных\n",
    "- <a href=\"http://habrahabr.ru/post/264407/\">Статья</a> на Хабрахабре про поиск недооцененных квартир\n",
    "- [Статья](https://habrahabr.ru/post/275963/) \"Python и красивые ножки: как я бы знакомил сына с математикой и программированием\" на Хабрахабре\n",
    "- [Статья](https://habrahabr.ru/post/270449/) \"Некоторые репозитории в помощь изучающим и преподающим Python и машинное обучение\" на Хабрахабре\n",
    "- [Курс](https://github.com/Yorko/python_intro) Python, основных алгоритмов и структур данных в виде тетрадок IPython\n",
    "- [Статья](https://habrahabr.ru/company/mlclass/blog/252743/) \"Ваш персональный курс по Big Data\" на Хабрахабре"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  },
  "name": "lesson8_part4_habr_girls.ipynb"
 },
 "nbformat": 4,
 "nbformat_minor": 1
}