answer.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 中途採用者実課題1問目解答\n",
    "\n",
    "まずデータを読み込んで各素性の頻度を見ることにより、全体的な傾向を調査します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "len= 5497\n",
      "type\n"
     ]
    },
    {
     "data": {
      "image/png": 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AJKmjDABJ6igDQJI6at4ASLI3yZtJnhuoXZDkUJKX2uv5rZ4kX0gyleSZJB8b6LO9tX8p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\nygCQpI4yACSpowwASeooA0CSOur/ARy3ejyxiqjVAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f347c581dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fixed.acidity\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3474e96cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "volatile.acidity\n"
     ]
    },
    {
     "data": {
      "image/png": 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QpEZZAJLUKAtAkhplAUhSoywASWqUBSBJjVqz2gGk5di0846JH2PHlmNcs8BxDt38gYkf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\nAUhSoywASWrU/wfbMd82c9OjcgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3474e1dfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "citric.acid\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3474dabef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "residual.sugar\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3474d24898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "chlorides\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3474c99a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "free.sulfur.dioxide\n"
     ]
    },
    {
     "data": {
      "image/png": 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DR6fZ5k5gJ8D4+HhNTEwMNLdOp8OOx94caN2laNuGE+x4bvbDdfjWibM/mQXS6XQY9Pgu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\ngSQJw0CShGEgScIwkCRhGEiSgP8LGdV/X7+MtB4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3474c1ea20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total.sulfur.dioxide\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3474b9afd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "density\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3474b12ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pH\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3474a8b908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sulphates\n"
     ]
    },
    {
     "data": {
      "image/png": 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MMuUAMDPLlAPAzCxTDgAzs0w5AMzMMuUAMDPLlAPAzCxTDgAzs0w5AMzMMuUAMDPLlAPA\nzCxTDgAzs0xNKwAk7Za0Q9JDkh5IbSdI2iTp8fRzRmqXpOsljUraLumMMjbAzMympox3AEMRcVpE\nDKTnq4HNETEP2JyeA5wDzEuPlcBXS1i3mZlNUSdOAS0F1qfp9cC5hfYbo2YrcLykWR1Yv5mZtWC6\nARDA9yRtk7QytfVHxD6A9PPE1D4beKaw7J7UZmZmXaCImPrC0psjYq+kE4FNwOXAhog4vtDnhYiY\nIelO4IsRcU9q3wz8RURsqxtzJbVTRPT39y8YHh6ecn07nn3xNW39R8P+l6c8ZKV6pdb+o+HEE47r\ndhktGRsbo6+vr9tltMS1lq9X6oTp1To0NLStcFp+UodPafQkIvamn89Jug1YCOyXNCsi9qVTPM+l\n7nuAOYXFTwL2NhhzDbAGYGBgIAYHB6dc34rVd76mbdX8ca7dMa3Nrkyv1Lpq/jgfncbvqUojIyNM\n55iqkmstX6/UCdXUOuVTQJKOkXTsxDRwNvAIsAFYnrotB25P0xuAj6W7gc4CXpw4VWRmZtWbzsvL\nfuA2SRPj/HNE/Juk+4GbJV0MPA2cl/pvBJYAo8BLwEXTWLeZmU3TlAMgIp4E3t2g/SfABxq0B3Dp\nVNdnZmbl8ieBzcwy5QAwM8uUA8DMLFMOADOzTDkAzMwy5QAwM8uUA8DMLFMOADOzTB36XzRjPWFu\ng+9dqsLuaz7UlfWavR74HYCZWaYcAGZmmXIAmJllygFgZpYpB4CZWaYcAGZmmXIAmJllygFgZpYp\nB4CZWaYcAGZmmXIAmJllygFgZpYpB4CZWaYcAGZmmXIAmJllygFgZpYpB4CZWaYq/49gkhYD/wAc\nBnw9Iq6pugZ7/Wj3P5Gtmj/OipL+e5n/G5n1ukrfAUg6DLgBOAc4BThf0ilV1mBmZjVVnwJaCIxG\nxJMR8b/AMLC04hrMzIzqTwHNBp4pPN8DnFlxDWalaPf0U7smO13lU09WFkVEdSuTzgMWRcQl6fmF\nwMKIuLzQZyWwMj19B/BYyWXMBJ4vecxO6ZVae6VOcK2d0iu19kqdML1a3xoRb2rWqep3AHuAOYXn\nJwF7ix0iYg2wplMFSHogIgY6NX6ZeqXWXqkTXGun9EqtvVInVFNr1dcA7gfmSTpZ0pHAMmBDxTWY\nmRkVvwOIiHFJlwF3UbsNdF1E7KyyBjMzq6n8cwARsRHYWPV6Czp2eqkDeqXWXqkTXGun9EqtvVIn\nVFBrpReBzczs0OGvgjAzy9TrJgAkLZb0mKRRSasbzP8zSY9K2i5ps6S3Fua9Kumh9Oj4RekWal0h\n6b8LNV1SmLdc0uPpsfwQqPW6Qp0/lvTTwrzK9qukdZKek/TIJPMl6fq0HdslnVGYV/U+bVbrBanG\n7ZJ+KOndhXm7Je1I+/SBQ6DWQUkvFn7Pf12Yd9Bjp+I6/7xQ4yPp2Dwhzat6n86RtEXSLkk7JX2q\nQZ9qjteI6PkHtQvKTwBvA44EHgZOqeszBLwxTf8p8O3CvLFDrNYVwD82WPYE4Mn0c0aantHNWuv6\nX07twn439uvvAWcAj0wyfwnwXUDAWcC93dinLdb6nokaqH1tyr2FebuBmYfQfh0E7pjusdPpOuv6\nfhi4u4v7dBZwRpo+Fvhxg78BlRyvr5d3AE2/YiIitkTES+npVmqfQeiG6XwdxiJgU0QciIgXgE3A\n4g7VCe3Xej5wUwfrmVRE/AA4cJAuS4Ebo2YrcLykWVS/T5vWGhE/TLVAd4/VVvbrZCr92pc26+za\ncQoQEfsi4sE0/XNgF7VvSSiq5Hh9vQRAo6+YqN+hRRdTS9cJb5D0gKStks7tRIEFrdb6R+mt3y2S\nJj481+52TlfL60un1E4G7i40V7lfm5lsW6rep+2qP1YD+J6kbap9av5Q8LuSHpb0XUmnprZDcr9K\neiO1P5jfKTR3bZ9KmgucDtxbN6uS47Xy20A7RA3aGt7eJOlPgAHg9wvNb4mIvZLeBtwtaUdEPNGB\nOqG1Wv8VuCkiXpH0SWA98P4Wly1TO+tbBtwSEa8W2qrcr81Mti1V79OWSRqiFgDvKzS/N+3TE4FN\nkv4rvfrtlgepfe3AmKQlwL8A8zh09+uHgf+IiOK7ha7sU0l91ILo0xHxs/rZDRYp/Xh9vbwDaPoV\nEwCSPgh8DvjDiHhloj0i9qafTwIj1BK5a7VGxE8K9X0NWNDqsiVrZ33LqHtbXfF+bWaybal6n7ZE\n0u8AXweWRsRPJtoL+/Q54DZqp1q6JiJ+FhFjaXojcISkmRyi+5WDH6eV7VNJR1D74/+tiLi1QZdq\njteqLnx08kHtncyT1E5BTFxwOrWuz+nULkrNq2ufARyVpmcCj9PZi1Wt1DqrMP0RYGv86gLQU6nm\nGWn6hG7Wmvq9g9qFNHVrv6b1zGXyi5Uf4tcvqt3XjX3aYq1vAUaB99S1HwMcW5j+IbC4y7X+5sTv\nndofzqfTPm7p2KmqzjT/OGrXCY7p5j5N++dG4O8P0qeS47WjB06VD2pXzX9M7Y/851Lb56m92gf4\nPrAfeCg9NqT29wA70gG6A7j4EKj1i8DOVNMW4LcLy348/XEYBS7qdq3p+ZXANXXLVbpfqb2q2wf8\nH7VXSRcDnwQ+meaL2j8jeiLVM9DFfdqs1q8DLxSO1QdS+9vS/nw4HR+fOwRqvaxwrG6lEFqNjp1u\n1Zn6rACG65brxj59H7XTNtsLv+Ml3The/UlgM7NMvV6uAZiZWZscAGZmmXIAmJllygFgZpYpB4CZ\nWaYcAGZmmXIAmJllygFgZpap/wfDDQvg8t5jeQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3474a062b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alcohol\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f34749fac50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quality\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3474b0e208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "wine = pd.read_csv(\"wine_train.csv\")\n",
    "wine.head\n",
    "print ( \"len=\", len(wine.index))\n",
    "for column in wine.columns:\n",
    "    print(column)\n",
    "    #plt.figure()\n",
    "    wine[column].hist()    \n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "wine.type=\"R\" (red) と wine.type=\"W\" (white) でデータ数にかなり違いがあることが分かります。\n",
    "また、目的変数である　quality が高いデータ（qualit=7,8,9）が少ないことが分かります。\n",
    "赤ワインと白ワインでは作り方が違うので、要求される特性が異なることが考えられます。\n",
    "赤ワインと白ワインに分けて、素性の頻度の違いを見てみます。\n",
    "赤と白でデータ数が違うので頻度（ｙ軸）は正規化せず、値（X軸）を共通にしています。\n",
    "白ワインは青で、赤ワインは赤の棒グラフで表示します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "type\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e74851d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fixed.acidity\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e9437b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "volatile.acidity\n"
     ]
    },
    {
     "data": {
      "image/png": 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Ht9aXKiNudweZ1Uj1rZYAmyPizlz79NxmXwNGVttbASyQdLikE8hqZj1fVrxmzfCZAFB0\nocsSf7hYe50NXAq8JGlDavs2sFDSbLKunreAbwBExCZJy4FXyEYWXeORQdYtnATMakTEc9Tv5185\nzntuA26bsqDMpoi7g8zMKsxJwMyswpwEzMwqzEnAzKzCnATMzCrMScDMrMIKJYFUJ2WHpJdzbUdL\nWiXptXR/VGqXpLtTWd2Nkk7PvWdR2v41SYta/3XMzGwyip4J3A/MrWm7EXg6ImYBT6fnABeSzZic\nRVYn5R7IkgbZIvVnkVVYvDlXgMvMzNqgUBKIiGeBnTXN84Fl6fEy4Ku59gcisxqYlqbbXwCsioid\nEfE+sIrRicXMzErUzDWB3ojYBln9deC41D5WWV2X2zUz6zBTUTZirLK6hcrtwv4ld3t7e5sqpdrK\nirpFw3DZ2nJ1a9xmnaCZJLBd0vSI2Ja6e3ak9rHK6m4FBmvah+vtOF9yd2BgoKmSu62sqFu0gJzL\n1parW+M26wTNdAetAEZG+CwCnsy1X5ZGCc0BPkjdRT8Gzpd0VLogfH5qMzOzNil0JiDpIbJf8cdK\n2ko2yud2YLmkK4FfA5ekzVcC88jWWf0YuAIgInZKuhV4IW13S0TUXmw2M7MSFUoCEbFwjJfOq7Nt\nANeMsZ+lwNLC0ZmZ2ZTyjGEzswpzEjCrIWmGpGckbZa0SdJ1qX3Ss+TNOp2TgNloe4BvRcQfAHOA\naySdzCRnyZt1AycBsxoRsS0i1qfHHwGbySY2TnaWvFnH8xrDZuOQNBM4DVhDzSx5SRPNkt9Ws6+9\nkyB7enqmdoJbK2dJ5uzq62O4VfsucYJft04oLCNuJwGzMUj6NPAYcH1EfCjVm/SebVqnbdTUwvwk\nyP7+/qYmQU6olbMkc4YXL2ZwaKg1Oys6+7IFunVCYRlxuzvIrA5Jh5IlgAcj4vHUvH2km6fgLHmz\njuckYFZD2U/+JcDmiLgz99JkZ8mbdTx3B5mNdjZwKfCSpA2p7dtMcpa8WTdwEjCrERHPUb+fHyY5\nS96s07k7yMyswpwEzMwqzEnAzKzCnATMzCrMScDMrMKcBMzMKsxJwMyswpwEzMwqrOEkIKlf0obc\n7UNJ10v6jqR3cu3zcu+5KS288aqkC1rzFczMrFENzxiOiFeB2QCSDgbeAZ4gmzJ/V0TsV282Lcqx\nADgF+DzwU0knRcQnjcZgZmbNaVV30HnA6xHxt+NsMx94OCJ2R8SbZHVWzmzR55uZWQNalQQWAA/l\nnl+b1lpdOrIOK2MvvGFmZm3SdAE5SYcBFwE3paZ7gFvJFtW4FbgD+DoFF95I+9y7AlNvb29TK+u0\ncoGlomF4FaNydWvcZp2gFVVELwTWR8R2gJF7AEn3AU+lp4UX3sivwDQwMNDUCkytXGCp6EJIXsWo\nXN0at1knaEV30EJyXUE1C2x/DXg5PV4BLJB0uKQTgFnA8y34fDMza1BTSUDSPwL+KfB4rvm/SHpJ\n0kbgHODfAUTEJmA58ArwI+AajwyyTpSuZe2Q9HKuzUOf7YDUVHdQRHwMHFPTduk4298G3NbMZ5qV\n4H7gu8ADNe0e+mwHHM8YNqsREc8COwtu7qHP1tWcBMyK89BnO+B4jWGzYlo69Lmnp2dqh7W2cmx0\nzq6+PoZbte8Sh/V26zDiMuJ2EjAroNVDn/v7+5sa+jyhVo6NzhlevJjBoaHW7KzomOsW6NZhxGXE\n7e4gswI89NkOVD4TMKsh6SFgEDhW0lbgZmBQ0myyrp63gG9ANvRZ0sjQ5z146LN1GScBsxoRsbBO\n85JxtvfQZ+ta7g4yM6swJwEzswpzEjAzqzAnATOzCuvaC8OqN0XHzMwmxWcCZmYV5iRgZlZhXdsd\nZGZdrpE+3RJLTVSFzwTMzCrMScDMrMKcBMzMKqzpJCDprbSm8AZJa1Pb0ZJWSXot3R+V2iXp7rQe\n60ZJpzf7+WZm1rhWnQmcExGzI2IgPb8ReDoiZgFPp+cAF5KV2p1FtrjGPS36fDMza8BUdQfNB5al\nx8uAr+baH4jMamBaTZ12MzMrUSuSQAA/kbQuLZ8H0BsR2wDS/XGp3euxmpl1kFbMEzg7It6VdByw\nStIvx9m20Hqs+bVYe3t7666xOUVLqI6r6FKfXs+0XN0at1knaDoJRMS76X6HpCeAM4HtkqZHxLbU\n3bMjbV5oPdb8WqwDAwN112KdoiVUx1V0norXMy1Xq+OWtBT4CrAjIk5NbUcDjwAzyVYW+5OIeF+S\ngL8A5gEfA5dHxPqWBWM2xZrqDpJ0pKTPjDwGzidbe3UFsChttgh4Mj1eAVyWRgnNAT4Y6TYy6yD3\nA3Nr2jzYwQ5IzZ4J9AJPZD+GOAT4fkT8SNILwHJJVwK/Bi5J268k+8W0hexX0xVNfr5Zy0XEs5Jm\n1jTPJ1t3GLLBDsPADeQGOwCrJU0bOQsuJ1qz5jSVBCLiDeCLddrfA86r0x7ANc18plmb7DfYIV0D\ng7EHOzgJWFdwATmz5hQa7AD7D3jo6emZ2ovZUzRyYldfH8PtGJUxosF/s24dPFBG3E4CZsU0NdgB\n9h/w0N/fX3fAQ8tM0ciJ4cWLGRwampJ9F9JgFVEPehibaweZFePBDnZA8pmAWQ1JD5FdBD5W0lbg\nZuB2PNjBDkBOAmY1ImLhGC95sIMdcNwdZGZWYU4CZmYV5iRgZlZhTgJmZhXmJGBmVmFOAmZmFeYk\nYGZWYU4CZmYV5slik6B6pcJqNFjaxMysLXwmYGZWYU4CZmYV5iRgZlZhviZg1umKXIwya5DPBMzM\nKqzhJCBphqRnJG2WtEnSdan9O5LekbQh3ebl3nOTpC2SXpV0QSu+gJmZNa6Z7qA9wLciYr2kzwDr\nJK1Kr90VEfstRCrpZGABcArweeCnkk6KiE+aiMHMzJrQ8JlARGyLiPXp8UfAZuD4cd4yH3g4InZH\nxJtkKzGd2ejnm7WDpLckvZTOctemtqMlrZL0Wro/qt1xmhXVkmsCkmYCpwFrUtO1kjZKWpr7D3E8\n8HbubVsZP2mYdapzImJ2RAyk5zcCT0fELODp9NysKzQ9OkjSp4HHgOsj4kNJ9wC3ApHu7wC+DtQb\n4lB3fq2kq4CrAHp7exkeHh61zeLFo5o6wvAw7Nq1q27Mnc5xN2w+2ZrEAMuAYeCGdgVjNhlNJQFJ\nh5IlgAcj4nGAiNiee/0+4Kn0dCswI/f2PuDdevuNiHuBewEGBgZicHBw1DbnnNNM5FMnAoaHh6kX\nc6dz3IUE8BNJAfzPdKz2RsQ2yLpJJR1XVjBmzWo4CUgSsATYHBF35tqnj/yHAL4GvJwerwC+L+lO\nsgvDs4DnG/18szY5OyLeTX/oV0n6ZdE35s9we3p6ip+9dNBp766+PobbGU+DZ3wdcLbYkDLibuZM\n4GzgUuAlSRtS27eBhZJmk/1iegv4BkBEbJK0HHiFbGTRNR4ZZN0mIt5N9zskPUE2uGH7yI8fSdOB\nHWO8d+8Zbn9/f90z3Lo66LR3ePFiBoeG2hdAgxUafZY7toaTQEQ8R/1+/pXjvOc24LZGP9OsnSQd\nCRwUER+lx+cDt5Cd5S4Cbk/3T7YvSrPJcdkIs+J6gSeynlAOAb4fET+S9AKwXNKVwK+BS9oYo9mk\nOAmYFRQRbwBfrNP+HnBe+RGZNc+1g8yse0iN3WxMTgJmZhXmJGBmVmFOAmZmFeYkYGZWYU4CZmYV\n5iRgZlZhTgJmZhXmJGBmVmFOAi0mwbp1nrtiZt3BScDMrMKcBMzMKsxJwMwOfEX6aCvaZ+skYGZW\nYS4l3SZFfmg0uIiSmVlhPhMwM6uw0pOApLmSXpW0RdKNZX++2VTxsW3dqNQkIOlg4C+BC4GTyRal\nP7nMGMymgo9t61ZlnwmcCWyJiDci4v8BDwPzS47BbCr42D7QVGQVs7KTwPHA27nnW1Ob1dHK4+0A\nPHY7jY9tyzSaPOrdxhva2iJljw6qF/moMTCSrgKuAo4Fdkl6daoDa6WhIY4F/q6Mz2rlH+9zzikv\n7hZrJu7fb1EMEx7bueMaYLekl1v02eUZGurOY+RAjHv8//yFj+uyk8BWYEbueR/wbu1GEXEvcK+k\ntRExs6TYWibFPdDuOCbLcTdlwmN75LiGjol50hx3ucqIu+zuoBeAWZJOkHQYsABYUXIMZlPBx7Z1\npVLPBCJij6RrgR8DBwNLI2JTmTGYTQUf29atSp8xHBErgZUFN793KmOZQo67XB0Rt4/tjua4x6Bw\nbQIzs8py2QgzswrriCQw0XR7SYdLeiS9vkbSzPKjHK1A3JdL+r+SNqTbv2pHnLUkLZW0Y6whisrc\nnb7XRkmnlx1jPQXiHpT0Qe7f+z+VHWNNPF15XEN3Hts+rhsUEW29kV1Eex34AnAY8CJwcs02/xr4\nXnq8AHikS+K+HPhuu2OtE/uXgdOBl8d4fR7wQ7Kx73OANe2OuWDcg8BT7Y5zEsdHxx3Xk4i9445t\nH9eN3TrhTKDIdPv5wLL0+FHgPKntc1y7tkxARDwL7Bxnk/nAA5FZDUyTNL2c6MZWIO5O0q3HNXTp\nse3jujGdkASKTLffu01E7AE+AI4pJbqxFS0T8M/TqeejkmbUeb0TdXMJhH8i6UVJP5R0Shvj6Nbj\nGg7cY9vHdR2dkASKlJIoVG6iZEVi+t/AzIj4Q+Cn7PvV1+k68d+7iPXA70fEF4H/DvygjbF063EN\nB+6x3an/3hOZ0uO6E5JAkVISe7eRdAjwOdrfLVCkTMB7EbE7Pb0POKOk2JpVqLxHp4mIDyNiV3q8\nEjhU0rFtCqdbj2s4cI9tH9d1dEISKDLdfgWwKD2+GPhZpCsmbTRh3DX9jRcBm0uMrxkrgMvSaIo5\nwAcRsa3dQU1E0j8e6VOXdCbZ8f1em8Lp1uMaDtxj28d1HW1fYzjGmG4v6RZgbUSsAJYAfy1pC9kv\npQXtizhTMO5/K+kiYA9Z3Je3LeAcSQ+RjTg4VtJW4GbgUICI+B7ZrNd5wBbgY+CK9kS6vwJxXwx8\nU9Ie4O+BBe36o9qtxzV077Ht47rBz++MHx5mZtYOndAdZGZmbeIkYGZWYU4CZmYV5iRgZlZhTgJm\nZhXmJGBmVmFOAmZmFeYkYGZWYf8fnA4UrOJ5Zq4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e6836438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "citric.acid\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e690ba90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "residual.sugar\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e9d46a20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "chlorides\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e9b24e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "free.sulfur.dioxide\n"
     ]
    },
    {
     "data": {
      "image/png": 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PAUTEPklbgCfJTqeui4i3O561WQvM2BQiYnVJeOMUY+8hOwdbtm4n8OGjys6sCyLiQcqv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\nmJlZ7v8DncFRo00qzwQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e94cda20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total.sulfur.dioxide\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e92d2a20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "density\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e9c4ad68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pH\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e6905898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sulphates\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e9e1a7f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alcohol\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e965fb38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quality\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e71dee80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "white = wine[wine.type=='W']\n",
    "red   = wine[wine.type=='R']\n",
    "\n",
    "# histgram\n",
    "for column in wine.columns:\n",
    "    print(column)\n",
    "    fig, (ax1,ax2) = plt.subplots(1, 2, sharex=True)\n",
    "    white[column].hist(color=\"blue\", ax=ax1)\n",
    "    red[column].hist(  color=\"red\", ax=ax2)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "多くの素性において、赤と白で値のばらつき方が異なることがわかりました。\n",
    "次にどの素性がquality に聞いているか、quality 別の頻度を見てみます。これも赤と白で分けてみてみます。\n",
    "quality= 7,8,9　の時の素性の値（の平均値）が、それ以外の時の値と異なるかに注目します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e94644e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e94ea0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e9e38748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e93f6be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e9665390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e9cdca58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e9b485f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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vKm3WvL9XaaMm/b+izg45Fqq0U/Njo0obHXasVG2vN1/MlvQdsmdU9QXuIvtG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\n/wc7+WKR36Se6gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e9da2e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e9b3d390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e954be80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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0LXAB8M3M/Ks2xhy/C2UAvwXcD5CZH6lQ8th5zqFxGIRNmXlPhXHeBWzOzJ9GxOHAtcA7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\nSYUw0CWpEP8PsKFM2BvYDEEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e93f6c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for column in wine.columns:\n",
    "    if column != 'type' and column != 'quality':\n",
    "         fig, (ax1,ax2) = plt.subplots(1, 2, sharey=True)\n",
    "         column_by_quality = white.groupby('quality').aggregate({column:np.mean}).reset_index()\n",
    "         column_by_quality.plot.bar(x='quality', color=\"blue\", ax=ax1 )\n",
    "         # plt.show()\n",
    "         column_by_quality = red.groupby('quality').aggregate({column:np.mean}).reset_index()\n",
    "         column_by_quality.plot.bar(x='quality', color=\"red\", ax=ax2 )\n",
    "         if( column == \"density\"):\n",
    "            plt.ylim([0.98, 1.0])\n",
    "         if( column == \"pH\"):\n",
    "            plt.ylim([3.0,3.5])\n",
    "         plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "赤では volatile.acidity,  citric.acid, chlorides, density, pH, sulphates, alcohol などが効いているようです。\n",
    "白では chlorides,  density, alcohol が効いているようです。\n",
    "この観察結果を相関係数を計算することにより確認します。\n",
    "各説明変数とquality の間の相関だけでなく、説明変数間の相関も見てみます。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "white correlation\n"
     ]
    },
    {
     "data": {
      "image/png": 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VfzJZSWm0f/imojIp67fxZe/7mXfJQ5w/ZjCOAL+zWvWTqoDzM6JfB/IOHCJj4/aKqfOZ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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e9ddae48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "red correlation\n"
     ]
    },
    {
     "data": {
      "image/png": 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ASPsmtH7mVhyeHmQkJLGw/yQclbzo8cU4PLw9MZ4e7P9+LVufL5s214hsQdOJ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\niIiImIX+P6olLOj6NjHqAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f00e9ac4588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn\n",
    "print( \"white correlation\")\n",
    "plt.figure(figsize=(15,15))\n",
    "seaborn.heatmap(white.corr(), annot=True)\n",
    "plt.show()\n",
    "\n",
    "print( \"red correlation\")\n",
    "plt.figure(figsize=(15,15))\n",
    "seaborn.heatmap(red.corr(), annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "白ワインについて、quality と相関があるのは大きい順に　alcohol, density(負の相関)　であることがわかります。\n",
    "赤ワインについては quality と相関があるのは大きい順に alcohol, volatile.acidity(負の相関), sulphates であることが分かります。\n",
    "ほぼ、ヒストグラムによる分析結果と一致しています。\n",
    "\n",
    "説明変数間の相関は、白ワインでは density とalcohol,  dnsity と residual.sugar　間で高いことが分かります。 \n",
    "赤ワインでは、densityとfixed.acidity、densityとpH 間で高いようですが、白ワインのそれより低いようです。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "上記観察を踏まえて学習モデルを作ります。\n",
    "赤ワイン、白ワイン別に準備した予測モデルを適用することにします。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "まず白ワイン用にquality を予測する予測器を作ります。\n",
    "quality=3～9 別に夫々分類器を作ることも考えられますが、quality=3 や 9 の頻度が少ないのでうまく作れません。\n",
    "ワインタイプを除いて説明変数は連続量であり quality も連続量と見なせるので、ここでは回帰モデル（RandomForestRegressor）を利用します。\n",
    "ハイパーパラメータ n_estimators と max_depth のチューニングのため、いくつかの組み合わせで最も良い平均二乗誤差(MSE)を出すものを見つけます。\n",
    "時間がかかるのでクロスバリデーションは 3 とします。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 3 folds for each of 12 candidates, totalling 36 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Done  36 out of  36 | elapsed:   30.5s finished\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'max_depth': 50, 'n_estimators': 100}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "# quality を　float に変換する。\n",
    "white = wine[wine.type=='W']\n",
    "white2 = white.copy()\n",
    "floatQuality = white['quality'].astype('float')\n",
    "white2.drop('quality', axis=1)\n",
    "white2['quality'] = floatQuality\n",
    "#print(white2)\n",
    "\n",
    "\n",
    "Y= white2.quality.values\n",
    "#print(Y)\n",
    "X = white2\n",
    "X=X.drop('quality', axis=1)\n",
    "X=X.drop('type', axis=1)\n",
    "X = X.as_matrix()\n",
    "#print(X)\n",
    "\n",
    "rfr_white = RandomForestRegressor(random_state=1234)\n",
    "params = { 'n_estimators':[10,50,100], 'max_depth':[5,10,50,100]}\n",
    "gscv = GridSearchCV( rfr_white, param_grid=params, verbose=1, cv=3, scoring='neg_mean_squared_error')\n",
    "gscv.fit(X,Y)\n",
    "gscv.best_params_\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "n_estimators は100, max_depth は 50で良いようです。\n",
    "訓練データ全部を使って学習します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 6.08  5.87  5.21 ...,  6.89  6.59  5.02]\n",
      "[ 6.  6.  5. ...,  7.  7.  5.]\n"
     ]
    }
   ],
   "source": [
    "rfr_white = RandomForestRegressor(n_estimators=100, max_depth=50, random_state=1234)\n",
    "rfr_white.fit(X,Y)\n",
    "y_pred = rfr_white.predict(X)\n",
    "print(y_pred)\n",
    "print(Y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "大体うまく予測できているようです。最終的にはRandomForestRegressorの出力を四捨五入してquality の予測値とします。\n",
    "どの素性が効いているか確認します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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63/RpHOK1+szMaqTH9VAlvRc4FtgPuEDSrhHxMvC0pE+mMpK0b6oyBzglbZ/W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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3469befb38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "imp = rfr_white.feature_importances_\n",
    "names = [ 'fixed.acidity', 'volatile.acidity', 'citric.acid',\n",
    "       'residual.sugar', 'chlorides', 'free.sulfur.dioxide',\n",
    "       'total.sulfur.dioxide', 'density', 'pH', 'sulphates', 'alcohol' ] \n",
    "    \n",
    "imp, names = zip(*sorted(zip(imp, names)))\n",
    " \n",
    "plt.barh(range(len(names)), imp, align='center')\n",
    "plt.yticks(range(len(names)), names)\n",
    " \n",
    "plt.xlabel('Importance of features')\n",
    "plt.ylabel('Features')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "alcohol, volatile.acidity, free.sulfur.dioxide 等が効いていることが分かります。density はあまり効いていません。density は alcohol と相関が高く主要な情報は alcohol から取得できるので、素性としての重要度が低いようです。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "次に、赤ワインのquality 予測器を作成します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 3 folds for each of 12 candidates, totalling 36 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Done  36 out of  36 | elapsed:   12.5s finished\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'max_depth': 50, 'n_estimators': 100}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "# quality を　float に変換する。\n",
    "red = wine[wine.type=='R']\n",
    "red2 = red.copy()\n",
    "floatQuality = red['quality'].astype('float')\n",
    "red2.drop('quality', axis=1)\n",
    "red2['quality'] = floatQuality\n",
    "\n",
    "\n",
    "\n",
    "Y= red2.quality.values\n",
    "#print(Y)\n",
    "X = red2\n",
    "X=X.drop('quality', axis=1)\n",
    "X=X.drop('type', axis=1)\n",
    "X = X.as_matrix()\n",
    "#print(X)\n",
    "\n",
    "rfr_red = RandomForestRegressor(random_state=1234)\n",
    "params = { 'n_estimators':[10,50,100], 'max_depth':[5,10,50,100]}\n",
    "gscv = GridSearchCV( rfr_red, param_grid=params, verbose=1, cv=3, scoring='neg_mean_squared_error')\n",
    "gscv.fit(X,Y)\n",
    "gscv.best_params_\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "こちらも　n_estimators は100, max_depth は 50で良いようです。\n",
    "訓練データ全部を使って学習します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 7.14  5.03  5.32 ...,  5.02  7.52  5.03]\n",
      "[ 7.  5.  5. ...,  5.  8.  5.]\n"
     ]
    }
   ],
   "source": [
    "rfr_red = RandomForestRegressor(n_estimators=100, max_depth=50, random_state=1234)\n",
    "rfr_red.fit(X,Y)\n",
    "y_pred = rfr_red.predict(X)\n",
    "print(y_pred)\n",
    "print(Y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "大体うまく予測できているようです。\n",
    "どの素性が効いているか確認します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AMRGxF9AMfFXSFsDRwG4RsTvw3TJ1XAGcHhF7d+C6Z6WdB3YHDpS0ezv5JwF7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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3469d47dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "imp = rfr_red.feature_importances_\n",
    "names = [ 'fixed.acidity', 'volatile.acidity', 'citric.acid',\n",
    "       'residual.sugar', 'chlorides', 'free.sulfur.dioxide',\n",
    "       'total.sulfur.dioxide', 'density', 'pH', 'sulphates', 'alcohol' ]\n",
    "#print(names)\n",
    "\n",
    "imp, names = zip(*sorted(zip(imp, names)))\n",
    " \n",
    "plt.barh(range(len(names)), imp, align='center')\n",
    "plt.yticks(range(len(names)), names)\n",
    " \n",
    "plt.xlabel('Importance of features')\n",
    "plt.ylabel('Features')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "alcohol, sulphates, volatile.acidity などが効いているようです。これは事前分析と合致しています。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "これまで作成した赤ワインのquality予測器、白ワインのqualityの予測器を合わせて本番データに適用します。\n",
    "得られた quality の推測値を、元データと合わせて \"result.tsv\" に出力します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "len= 1000\n"
     ]
    }
   ],
   "source": [
    "test = pd.read_csv(\"wine_test.csv\")\n",
    "#print(test)\n",
    "print ( \"len=\", len(test.index))\n",
    "\n",
    "myRound =lambda x:(x*2+1)//2\n",
    "\n",
    "out = []\n",
    "for index, row in test.iterrows():\n",
    "    #print(row['type'])\n",
    "    if( row['type'] == 'R'):\n",
    "        row = row.drop('type')\n",
    "        row = row.as_matrix()\n",
    "        y, = rfr_red.predict([row])\n",
    "        val= int( myRound(y))\n",
    "        out.append(val)\n",
    "    else:\n",
    "        row = row.drop('type')\n",
    "        row = row.as_matrix()\n",
    "        y, = rfr_white.predict([row])   \n",
    "        val =int(myRound(y))\n",
    "        out.append(val)\n",
    "test['quality']=out\n",
    "#test\n",
    "# tsv 出力\n",
    "test.to_csv('result.tsv', sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "以上です。"
   ]
  }
 ],
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