{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "02_machine_learning_enshu.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qvBSQgmhJxNc"
      },
      "source": [
        "### 機械学習　演習"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7L-SYR9eJ4Cj"
      },
      "source": [
        "#### ボストン住宅家賃予測\n",
        "#### 単純な線形回帰モデル(scikit learn)\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VwoxZLNsp0od"
      },
      "source": [
        "from sklearn.datasets import load_boston\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn.linear_model import LinearRegression\n",
        "import re\n",
        "import requests\n",
        "from pprint import pprint\n",
        "import lightgbm"
      ],
      "execution_count": 115,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9QQsxjmhqAAy",
        "outputId": "05d21d66-cb50-4d9e-8bc7-2692a619a9d1"
      },
      "source": [
        "print(np.__version__)"
      ],
      "execution_count": 116,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "1.19.5\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8uhhGhM3qICG"
      },
      "source": [
        "boston = load_boston()"
      ],
      "execution_count": 117,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8weuK7GLqXjt"
      },
      "source": [
        "# print(boston)"
      ],
      "execution_count": 118,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R-bmp0g0M-GF",
        "outputId": "852ec3cd-610e-420e-b005-fe2165b1ec75"
      },
      "source": [
        "# ディクショナリ型なので、keys()でデータ構成を確認できる。\n",
        "print(boston.keys())\n",
        "print(boston[\"feature_names\"])"
      ],
      "execution_count": 119,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "dict_keys(['data', 'target', 'feature_names', 'DESCR', 'filename'])\n",
            "['CRIM' 'ZN' 'INDUS' 'CHAS' 'NOX' 'RM' 'AGE' 'DIS' 'RAD' 'TAX' 'PTRATIO'\n",
            " 'B' 'LSTAT']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F6v-iS1uqn-w"
      },
      "source": [
        "# print(boston[\"DESCR\"])"
      ],
      "execution_count": 120,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "35Ol7MqnqvO6",
        "outputId": "a902474e-5a85-4bc6-ed65-817bbe6aca26"
      },
      "source": [
        "print(boston[\"feature_names\"])"
      ],
      "execution_count": 121,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['CRIM' 'ZN' 'INDUS' 'CHAS' 'NOX' 'RM' 'AGE' 'DIS' 'RAD' 'TAX' 'PTRATIO'\n",
            " 'B' 'LSTAT']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rJTY88hVqznv"
      },
      "source": [
        "boston_data = boston[\"data\"]"
      ],
      "execution_count": 122,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 453
        },
        "id": "WMowO6lYq9e6",
        "outputId": "655b4daf-bde4-4edd-e44e-13d4d099de69"
      },
      "source": [
        "columns = boston[\"feature_names\"]\n",
        "# columns = np.append(columns, \"MEDV\") MEDV列はtargetの方にある。\n",
        "df = pd.DataFrame(boston_data, columns=columns)\n",
        "print(columns)\n",
        "df"
      ],
      "execution_count": 123,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['CRIM' 'ZN' 'INDUS' 'CHAS' 'NOX' 'RM' 'AGE' 'DIS' 'RAD' 'TAX' 'PTRATIO'\n",
            " 'B' 'LSTAT']\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>CRIM</th>\n",
              "      <th>ZN</th>\n",
              "      <th>INDUS</th>\n",
              "      <th>CHAS</th>\n",
              "      <th>NOX</th>\n",
              "      <th>RM</th>\n",
              "      <th>AGE</th>\n",
              "      <th>DIS</th>\n",
              "      <th>RAD</th>\n",
              "      <th>TAX</th>\n",
              "      <th>PTRATIO</th>\n",
              "      <th>B</th>\n",
              "      <th>LSTAT</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.00632</td>\n",
              "      <td>18.0</td>\n",
              "      <td>2.31</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.538</td>\n",
              "      <td>6.575</td>\n",
              "      <td>65.2</td>\n",
              "      <td>4.0900</td>\n",
              "      <td>1.0</td>\n",
              "      <td>296.0</td>\n",
              "      <td>15.3</td>\n",
              "      <td>396.90</td>\n",
              "      <td>4.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.02731</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.469</td>\n",
              "      <td>6.421</td>\n",
              "      <td>78.9</td>\n",
              "      <td>4.9671</td>\n",
              "      <td>2.0</td>\n",
              "      <td>242.0</td>\n",
              "      <td>17.8</td>\n",
              "      <td>396.90</td>\n",
              "      <td>9.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.02729</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.469</td>\n",
              "      <td>7.185</td>\n",
              "      <td>61.1</td>\n",
              "      <td>4.9671</td>\n",
              "      <td>2.0</td>\n",
              "      <td>242.0</td>\n",
              "      <td>17.8</td>\n",
              "      <td>392.83</td>\n",
              "      <td>4.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.03237</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.18</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.458</td>\n",
              "      <td>6.998</td>\n",
              "      <td>45.8</td>\n",
              "      <td>6.0622</td>\n",
              "      <td>3.0</td>\n",
              "      <td>222.0</td>\n",
              "      <td>18.7</td>\n",
              "      <td>394.63</td>\n",
              "      <td>2.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.06905</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.18</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.458</td>\n",
              "      <td>7.147</td>\n",
              "      <td>54.2</td>\n",
              "      <td>6.0622</td>\n",
              "      <td>3.0</td>\n",
              "      <td>222.0</td>\n",
              "      <td>18.7</td>\n",
              "      <td>396.90</td>\n",
              "      <td>5.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>501</th>\n",
              "      <td>0.06263</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.593</td>\n",
              "      <td>69.1</td>\n",
              "      <td>2.4786</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>391.99</td>\n",
              "      <td>9.67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>502</th>\n",
              "      <td>0.04527</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.120</td>\n",
              "      <td>76.7</td>\n",
              "      <td>2.2875</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>396.90</td>\n",
              "      <td>9.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>503</th>\n",
              "      <td>0.06076</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.976</td>\n",
              "      <td>91.0</td>\n",
              "      <td>2.1675</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>396.90</td>\n",
              "      <td>5.64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>504</th>\n",
              "      <td>0.10959</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.794</td>\n",
              "      <td>89.3</td>\n",
              "      <td>2.3889</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>393.45</td>\n",
              "      <td>6.48</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>505</th>\n",
              "      <td>0.04741</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.030</td>\n",
              "      <td>80.8</td>\n",
              "      <td>2.5050</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>396.90</td>\n",
              "      <td>7.88</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>506 rows × 13 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        CRIM    ZN  INDUS  CHAS    NOX  ...  RAD    TAX  PTRATIO       B  LSTAT\n",
              "0    0.00632  18.0   2.31   0.0  0.538  ...  1.0  296.0     15.3  396.90   4.98\n",
              "1    0.02731   0.0   7.07   0.0  0.469  ...  2.0  242.0     17.8  396.90   9.14\n",
              "2    0.02729   0.0   7.07   0.0  0.469  ...  2.0  242.0     17.8  392.83   4.03\n",
              "3    0.03237   0.0   2.18   0.0  0.458  ...  3.0  222.0     18.7  394.63   2.94\n",
              "4    0.06905   0.0   2.18   0.0  0.458  ...  3.0  222.0     18.7  396.90   5.33\n",
              "..       ...   ...    ...   ...    ...  ...  ...    ...      ...     ...    ...\n",
              "501  0.06263   0.0  11.93   0.0  0.573  ...  1.0  273.0     21.0  391.99   9.67\n",
              "502  0.04527   0.0  11.93   0.0  0.573  ...  1.0  273.0     21.0  396.90   9.08\n",
              "503  0.06076   0.0  11.93   0.0  0.573  ...  1.0  273.0     21.0  396.90   5.64\n",
              "504  0.10959   0.0  11.93   0.0  0.573  ...  1.0  273.0     21.0  393.45   6.48\n",
              "505  0.04741   0.0  11.93   0.0  0.573  ...  1.0  273.0     21.0  396.90   7.88\n",
              "\n",
              "[506 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 123
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "id": "nMOXijHIroDv",
        "outputId": "2a36e3c7-4264-4e88-c1b5-5ba79c249aab"
      },
      "source": [
        "df.describe()"
      ],
      "execution_count": 124,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>CRIM</th>\n",
              "      <th>ZN</th>\n",
              "      <th>INDUS</th>\n",
              "      <th>CHAS</th>\n",
              "      <th>NOX</th>\n",
              "      <th>RM</th>\n",
              "      <th>AGE</th>\n",
              "      <th>DIS</th>\n",
              "      <th>RAD</th>\n",
              "      <th>TAX</th>\n",
              "      <th>PTRATIO</th>\n",
              "      <th>B</th>\n",
              "      <th>LSTAT</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>506.000000</td>\n",
              "      <td>506.000000</td>\n",
              "      <td>506.000000</td>\n",
              "      <td>506.000000</td>\n",
              "      <td>506.000000</td>\n",
              "      <td>506.000000</td>\n",
              "      <td>506.000000</td>\n",
              "      <td>506.000000</td>\n",
              "      <td>506.000000</td>\n",
              "      <td>506.000000</td>\n",
              "      <td>506.000000</td>\n",
              "      <td>506.000000</td>\n",
              "      <td>506.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>3.613524</td>\n",
              "      <td>11.363636</td>\n",
              "      <td>11.136779</td>\n",
              "      <td>0.069170</td>\n",
              "      <td>0.554695</td>\n",
              "      <td>6.284634</td>\n",
              "      <td>68.574901</td>\n",
              "      <td>3.795043</td>\n",
              "      <td>9.549407</td>\n",
              "      <td>408.237154</td>\n",
              "      <td>18.455534</td>\n",
              "      <td>356.674032</td>\n",
              "      <td>12.653063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>8.601545</td>\n",
              "      <td>23.322453</td>\n",
              "      <td>6.860353</td>\n",
              "      <td>0.253994</td>\n",
              "      <td>0.115878</td>\n",
              "      <td>0.702617</td>\n",
              "      <td>28.148861</td>\n",
              "      <td>2.105710</td>\n",
              "      <td>8.707259</td>\n",
              "      <td>168.537116</td>\n",
              "      <td>2.164946</td>\n",
              "      <td>91.294864</td>\n",
              "      <td>7.141062</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.006320</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.460000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.385000</td>\n",
              "      <td>3.561000</td>\n",
              "      <td>2.900000</td>\n",
              "      <td>1.129600</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>187.000000</td>\n",
              "      <td>12.600000</td>\n",
              "      <td>0.320000</td>\n",
              "      <td>1.730000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>0.082045</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5.190000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.449000</td>\n",
              "      <td>5.885500</td>\n",
              "      <td>45.025000</td>\n",
              "      <td>2.100175</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>279.000000</td>\n",
              "      <td>17.400000</td>\n",
              "      <td>375.377500</td>\n",
              "      <td>6.950000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>0.256510</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>9.690000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.538000</td>\n",
              "      <td>6.208500</td>\n",
              "      <td>77.500000</td>\n",
              "      <td>3.207450</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>330.000000</td>\n",
              "      <td>19.050000</td>\n",
              "      <td>391.440000</td>\n",
              "      <td>11.360000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>3.677083</td>\n",
              "      <td>12.500000</td>\n",
              "      <td>18.100000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.624000</td>\n",
              "      <td>6.623500</td>\n",
              "      <td>94.075000</td>\n",
              "      <td>5.188425</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>666.000000</td>\n",
              "      <td>20.200000</td>\n",
              "      <td>396.225000</td>\n",
              "      <td>16.955000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>88.976200</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>27.740000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.871000</td>\n",
              "      <td>8.780000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>12.126500</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>711.000000</td>\n",
              "      <td>22.000000</td>\n",
              "      <td>396.900000</td>\n",
              "      <td>37.970000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             CRIM          ZN       INDUS  ...     PTRATIO           B       LSTAT\n",
              "count  506.000000  506.000000  506.000000  ...  506.000000  506.000000  506.000000\n",
              "mean     3.613524   11.363636   11.136779  ...   18.455534  356.674032   12.653063\n",
              "std      8.601545   23.322453    6.860353  ...    2.164946   91.294864    7.141062\n",
              "min      0.006320    0.000000    0.460000  ...   12.600000    0.320000    1.730000\n",
              "25%      0.082045    0.000000    5.190000  ...   17.400000  375.377500    6.950000\n",
              "50%      0.256510    0.000000    9.690000  ...   19.050000  391.440000   11.360000\n",
              "75%      3.677083   12.500000   18.100000  ...   20.200000  396.225000   16.955000\n",
              "max     88.976200  100.000000   27.740000  ...   22.000000  396.900000   37.970000\n",
              "\n",
              "[8 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 124
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "J6M-vJ3Er26L",
        "outputId": "4a76e197-2dd5-411f-855c-73d7cae1b684"
      },
      "source": [
        "df.shape"
      ],
      "execution_count": 125,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(506, 13)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 125
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "tx8IR4e0r5nx",
        "outputId": "b9fc5c30-7d16-4d6a-c3b0-663c38bf432e"
      },
      "source": [
        "# 目的変数をDataFrameへ追加\n",
        "df['PRICE'] = np.array(boston.target)\n",
        "df"
      ],
      "execution_count": 126,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>CRIM</th>\n",
              "      <th>ZN</th>\n",
              "      <th>INDUS</th>\n",
              "      <th>CHAS</th>\n",
              "      <th>NOX</th>\n",
              "      <th>RM</th>\n",
              "      <th>AGE</th>\n",
              "      <th>DIS</th>\n",
              "      <th>RAD</th>\n",
              "      <th>TAX</th>\n",
              "      <th>PTRATIO</th>\n",
              "      <th>B</th>\n",
              "      <th>LSTAT</th>\n",
              "      <th>PRICE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.00632</td>\n",
              "      <td>18.0</td>\n",
              "      <td>2.31</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.538</td>\n",
              "      <td>6.575</td>\n",
              "      <td>65.2</td>\n",
              "      <td>4.0900</td>\n",
              "      <td>1.0</td>\n",
              "      <td>296.0</td>\n",
              "      <td>15.3</td>\n",
              "      <td>396.90</td>\n",
              "      <td>4.98</td>\n",
              "      <td>24.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.02731</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.469</td>\n",
              "      <td>6.421</td>\n",
              "      <td>78.9</td>\n",
              "      <td>4.9671</td>\n",
              "      <td>2.0</td>\n",
              "      <td>242.0</td>\n",
              "      <td>17.8</td>\n",
              "      <td>396.90</td>\n",
              "      <td>9.14</td>\n",
              "      <td>21.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.02729</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.469</td>\n",
              "      <td>7.185</td>\n",
              "      <td>61.1</td>\n",
              "      <td>4.9671</td>\n",
              "      <td>2.0</td>\n",
              "      <td>242.0</td>\n",
              "      <td>17.8</td>\n",
              "      <td>392.83</td>\n",
              "      <td>4.03</td>\n",
              "      <td>34.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.03237</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.18</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.458</td>\n",
              "      <td>6.998</td>\n",
              "      <td>45.8</td>\n",
              "      <td>6.0622</td>\n",
              "      <td>3.0</td>\n",
              "      <td>222.0</td>\n",
              "      <td>18.7</td>\n",
              "      <td>394.63</td>\n",
              "      <td>2.94</td>\n",
              "      <td>33.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.06905</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.18</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.458</td>\n",
              "      <td>7.147</td>\n",
              "      <td>54.2</td>\n",
              "      <td>6.0622</td>\n",
              "      <td>3.0</td>\n",
              "      <td>222.0</td>\n",
              "      <td>18.7</td>\n",
              "      <td>396.90</td>\n",
              "      <td>5.33</td>\n",
              "      <td>36.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>501</th>\n",
              "      <td>0.06263</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.593</td>\n",
              "      <td>69.1</td>\n",
              "      <td>2.4786</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>391.99</td>\n",
              "      <td>9.67</td>\n",
              "      <td>22.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>502</th>\n",
              "      <td>0.04527</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.120</td>\n",
              "      <td>76.7</td>\n",
              "      <td>2.2875</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>396.90</td>\n",
              "      <td>9.08</td>\n",
              "      <td>20.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>503</th>\n",
              "      <td>0.06076</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.976</td>\n",
              "      <td>91.0</td>\n",
              "      <td>2.1675</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>396.90</td>\n",
              "      <td>5.64</td>\n",
              "      <td>23.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>504</th>\n",
              "      <td>0.10959</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.794</td>\n",
              "      <td>89.3</td>\n",
              "      <td>2.3889</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>393.45</td>\n",
              "      <td>6.48</td>\n",
              "      <td>22.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>505</th>\n",
              "      <td>0.04741</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.030</td>\n",
              "      <td>80.8</td>\n",
              "      <td>2.5050</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>396.90</td>\n",
              "      <td>7.88</td>\n",
              "      <td>11.9</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>506 rows × 14 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        CRIM    ZN  INDUS  CHAS    NOX  ...    TAX  PTRATIO       B  LSTAT  PRICE\n",
              "0    0.00632  18.0   2.31   0.0  0.538  ...  296.0     15.3  396.90   4.98   24.0\n",
              "1    0.02731   0.0   7.07   0.0  0.469  ...  242.0     17.8  396.90   9.14   21.6\n",
              "2    0.02729   0.0   7.07   0.0  0.469  ...  242.0     17.8  392.83   4.03   34.7\n",
              "3    0.03237   0.0   2.18   0.0  0.458  ...  222.0     18.7  394.63   2.94   33.4\n",
              "4    0.06905   0.0   2.18   0.0  0.458  ...  222.0     18.7  396.90   5.33   36.2\n",
              "..       ...   ...    ...   ...    ...  ...    ...      ...     ...    ...    ...\n",
              "501  0.06263   0.0  11.93   0.0  0.573  ...  273.0     21.0  391.99   9.67   22.4\n",
              "502  0.04527   0.0  11.93   0.0  0.573  ...  273.0     21.0  396.90   9.08   20.6\n",
              "503  0.06076   0.0  11.93   0.0  0.573  ...  273.0     21.0  396.90   5.64   23.9\n",
              "504  0.10959   0.0  11.93   0.0  0.573  ...  273.0     21.0  393.45   6.48   22.0\n",
              "505  0.04741   0.0  11.93   0.0  0.573  ...  273.0     21.0  396.90   7.88   11.9\n",
              "\n",
              "[506 rows x 14 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 126
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EQPtZi9Ut1Hp"
      },
      "source": [
        ""
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WXSOTLQ2virD",
        "outputId": "1d18b52f-4007-4604-edd4-e125a6f77627"
      },
      "source": [
        "len(df['RM'].values)"
      ],
      "execution_count": 127,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "506"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 127
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OWh70h1iwA5G"
      },
      "source": [
        "explain = df[['RM']].values\n",
        "# explain"
      ],
      "execution_count": 128,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uCDPSVfvxZSy"
      },
      "source": [
        "target = df[['PRICE']].values\n",
        "# target"
      ],
      "execution_count": 129,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jncHdEyXw3dH",
        "outputId": "85b19bd6-b92b-4723-b826-6c273e91a096"
      },
      "source": [
        "model = LinearRegression()\n",
        "model.fit(explain, target)\n",
        "model.predict([[7]])"
      ],
      "execution_count": 130,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[29.04414209]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 130
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 743
        },
        "id": "6QhRsYH8NV-a",
        "outputId": "d784ef83-095c-4533-df70-068e0683accc"
      },
      "source": [
        "# 散布図行列でざっくり相関を確認\n",
        "%matplotlib inline\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "sns.pairplot(df[[\"RM\", \"AGE\", \"DIS\", \"PRICE\"]]) # seaborn.pariplotで散布図行列の描画"
      ],
      "execution_count": 131,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7ff11c7c1110>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 131
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 20 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dq-jfEiQj1Fm",
        "outputId": "729f2fe3-4ac2-4fbf-c550-156ebd66bb40"
      },
      "source": [
        "# 説明変数を追加\n",
        "explain = df[['RM','DIS']].values\n",
        "model = LinearRegression()\n",
        "model.fit(explain, target)\n",
        "model.predict([[7, 6]])"
      ],
      "execution_count": 132,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[29.90692384]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 132
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qDW5qM69lazx",
        "outputId": "922fc261-b2a5-4b2f-f7f7-769548b3201a"
      },
      "source": [
        "# さらに追加\n",
        "explain = df[['RM','DIS', 'ZN']].values\n",
        "model = LinearRegression()\n",
        "model.fit(explain, target)\n",
        "model.predict([[7, 6, 40]])"
      ],
      "execution_count": 133,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[30.4200297]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 133
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 316
        },
        "id": "t1-BK-vKludY",
        "outputId": "a928696b-fb61-401c-96d0-6445e45331e1"
      },
      "source": [
        "plt.hist(df['ZN'])"
      ],
      "execution_count": 134,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([372.,  12.,  48.,  16.,  13.,   6.,   4.,   6.,  19.,  10.]),\n",
              " array([  0.,  10.,  20.,  30.,  40.,  50.,  60.,  70.,  80.,  90., 100.]),\n",
              " <a list of 10 Patch objects>)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 134
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WmdGhVyBmB9Z",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "4b67e882-7b6b-413f-9d32-26ad87cb358e"
      },
      "source": [
        "df"
      ],
      "execution_count": 135,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>CRIM</th>\n",
              "      <th>ZN</th>\n",
              "      <th>INDUS</th>\n",
              "      <th>CHAS</th>\n",
              "      <th>NOX</th>\n",
              "      <th>RM</th>\n",
              "      <th>AGE</th>\n",
              "      <th>DIS</th>\n",
              "      <th>RAD</th>\n",
              "      <th>TAX</th>\n",
              "      <th>PTRATIO</th>\n",
              "      <th>B</th>\n",
              "      <th>LSTAT</th>\n",
              "      <th>PRICE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.00632</td>\n",
              "      <td>18.0</td>\n",
              "      <td>2.31</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.538</td>\n",
              "      <td>6.575</td>\n",
              "      <td>65.2</td>\n",
              "      <td>4.0900</td>\n",
              "      <td>1.0</td>\n",
              "      <td>296.0</td>\n",
              "      <td>15.3</td>\n",
              "      <td>396.90</td>\n",
              "      <td>4.98</td>\n",
              "      <td>24.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.02731</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.469</td>\n",
              "      <td>6.421</td>\n",
              "      <td>78.9</td>\n",
              "      <td>4.9671</td>\n",
              "      <td>2.0</td>\n",
              "      <td>242.0</td>\n",
              "      <td>17.8</td>\n",
              "      <td>396.90</td>\n",
              "      <td>9.14</td>\n",
              "      <td>21.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.02729</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.07</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.469</td>\n",
              "      <td>7.185</td>\n",
              "      <td>61.1</td>\n",
              "      <td>4.9671</td>\n",
              "      <td>2.0</td>\n",
              "      <td>242.0</td>\n",
              "      <td>17.8</td>\n",
              "      <td>392.83</td>\n",
              "      <td>4.03</td>\n",
              "      <td>34.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.03237</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.18</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.458</td>\n",
              "      <td>6.998</td>\n",
              "      <td>45.8</td>\n",
              "      <td>6.0622</td>\n",
              "      <td>3.0</td>\n",
              "      <td>222.0</td>\n",
              "      <td>18.7</td>\n",
              "      <td>394.63</td>\n",
              "      <td>2.94</td>\n",
              "      <td>33.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.06905</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2.18</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.458</td>\n",
              "      <td>7.147</td>\n",
              "      <td>54.2</td>\n",
              "      <td>6.0622</td>\n",
              "      <td>3.0</td>\n",
              "      <td>222.0</td>\n",
              "      <td>18.7</td>\n",
              "      <td>396.90</td>\n",
              "      <td>5.33</td>\n",
              "      <td>36.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>501</th>\n",
              "      <td>0.06263</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.593</td>\n",
              "      <td>69.1</td>\n",
              "      <td>2.4786</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>391.99</td>\n",
              "      <td>9.67</td>\n",
              "      <td>22.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>502</th>\n",
              "      <td>0.04527</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.120</td>\n",
              "      <td>76.7</td>\n",
              "      <td>2.2875</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>396.90</td>\n",
              "      <td>9.08</td>\n",
              "      <td>20.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>503</th>\n",
              "      <td>0.06076</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.976</td>\n",
              "      <td>91.0</td>\n",
              "      <td>2.1675</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>396.90</td>\n",
              "      <td>5.64</td>\n",
              "      <td>23.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>504</th>\n",
              "      <td>0.10959</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.794</td>\n",
              "      <td>89.3</td>\n",
              "      <td>2.3889</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>393.45</td>\n",
              "      <td>6.48</td>\n",
              "      <td>22.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>505</th>\n",
              "      <td>0.04741</td>\n",
              "      <td>0.0</td>\n",
              "      <td>11.93</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.573</td>\n",
              "      <td>6.030</td>\n",
              "      <td>80.8</td>\n",
              "      <td>2.5050</td>\n",
              "      <td>1.0</td>\n",
              "      <td>273.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>396.90</td>\n",
              "      <td>7.88</td>\n",
              "      <td>11.9</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>506 rows × 14 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        CRIM    ZN  INDUS  CHAS    NOX  ...    TAX  PTRATIO       B  LSTAT  PRICE\n",
              "0    0.00632  18.0   2.31   0.0  0.538  ...  296.0     15.3  396.90   4.98   24.0\n",
              "1    0.02731   0.0   7.07   0.0  0.469  ...  242.0     17.8  396.90   9.14   21.6\n",
              "2    0.02729   0.0   7.07   0.0  0.469  ...  242.0     17.8  392.83   4.03   34.7\n",
              "3    0.03237   0.0   2.18   0.0  0.458  ...  222.0     18.7  394.63   2.94   33.4\n",
              "4    0.06905   0.0   2.18   0.0  0.458  ...  222.0     18.7  396.90   5.33   36.2\n",
              "..       ...   ...    ...   ...    ...  ...    ...      ...     ...    ...    ...\n",
              "501  0.06263   0.0  11.93   0.0  0.573  ...  273.0     21.0  391.99   9.67   22.4\n",
              "502  0.04527   0.0  11.93   0.0  0.573  ...  273.0     21.0  396.90   9.08   20.6\n",
              "503  0.06076   0.0  11.93   0.0  0.573  ...  273.0     21.0  396.90   5.64   23.9\n",
              "504  0.10959   0.0  11.93   0.0  0.573  ...  273.0     21.0  393.45   6.48   22.0\n",
              "505  0.04741   0.0  11.93   0.0  0.573  ...  273.0     21.0  396.90   7.88   11.9\n",
              "\n",
              "[506 rows x 14 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 135
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xjX9OXIEG8lp"
      },
      "source": [
        "# 説明変数と目的変数を改めて準備\n",
        "explain = df[['RM','DIS', 'ZN']].values\n",
        "target = df[['PRICE']].values"
      ],
      "execution_count": 136,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xyo43RDiGZR4",
        "outputId": "a2d46941-d337-4d76-924e-e1da39c4ca6b"
      },
      "source": [
        "# 単純に学習と予測\n",
        "model = LinearRegression()\n",
        "model.fit(explain, target)\n",
        "print(\"score: \", model.score(explain, target)) # 学習データでのスコアでも0.5しかいかない。\n",
        "model.predict([[7, 6, 40]])\n"
      ],
      "execution_count": 137,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "score:  0.50658594274368\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[30.4200297]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 137
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_JaAANqQG5cv",
        "outputId": "b64eeb07-262d-4a0c-b184-33bc3652dcb8"
      },
      "source": [
        "# 分割\n",
        "from sklearn.model_selection import train_test_split\n",
        "X_train, X_test, y_train, y_test = \\\n",
        "    train_test_split(explain, target, random_state=0, train_size=0.7)\n",
        "print(len(X_train))\n",
        "print(len(X_test))\n",
        "\n",
        "model = LinearRegression()\n",
        "model.fit(X_train, y_train)\n",
        "print(\"score: \", model.score(X_test, y_test)) # 検証データだとさらに低い。0.44\n",
        "model.predict([[7, 6, 40]])"
      ],
      "execution_count": 138,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "354\n",
            "152\n",
            "score:  0.4444787511285049\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[30.66816442]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 138
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ueKVkQLWNm49",
        "outputId": "826c1051-faa2-4366-8a87-b64e3ba0fbb0"
      },
      "source": [
        "# このセルの、「cross_val_score」 は、スコアの種類が一度にひとつしか計算できないので使わないほうがよい。\n",
        "from sklearn.model_selection import cross_val_score\n",
        "explain = df[['RM','DIS', 'ZN']].values\n",
        "target = df[['PRICE']].values\n",
        "model = LinearRegression()\n",
        "scores = cross_val_score(model, explain, target)\n",
        "# 各分割におけるスコア\n",
        "print('Cross-Validation scores: {}'.format(scores))\n",
        "# スコアの平均値\n",
        "import numpy as np\n",
        "print('Average score: {}'.format(np.mean(scores)))"
      ],
      "execution_count": 139,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cross-Validation scores: [ 0.69636231  0.61903785  0.50149366 -0.19361097 -1.74396334]\n",
            "Average score: -0.024136097681940603\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kaglG7cF-Jr1",
        "outputId": "7d237de1-fb51-490e-a56f-4f9cc42640a2"
      },
      "source": [
        "# 交差検証\n",
        "# よくネットで見かける cross_val_scoreは、\n",
        "# スコアの種類を同時にいくつも計算してくれなくて使い勝手が悪いとのこと。\n",
        "# https://www.haya-programming.com/entry/2018/03/31/184557\n",
        "# https://blog.amedama.jp/entry/sklearn-cv-custom-metric\n",
        "# cross_validate を使用する\n",
        "from sklearn.model_selection import cross_validate, StratifiedKFold, KFold\n",
        "# from sklearn.model_selection import cross_val_score\n",
        "\n",
        "# このように複数の種類を指定できる、が、今回は回帰なので\n",
        "# これらの指標は関係なかった\n",
        "# scoring = {\"p\": \"precision_macro\", \"r\": \"recall_macro\", \"f\": \"f1_macro\"}\n",
        "# scoring = ['accuracy','precision','recall','f1']\n",
        "# ここに適切な指標を指定しないとcontinuous is not supported と分かりづらいエラーが出る。\n",
        "scoring = [\n",
        "  'neg_mean_squared_error',\n",
        "  'neg_median_absolute_error']\n",
        "# くわしい説明はここ\n",
        "# https://qiita.com/Mukomiz/items/f5c562ff8b538c1502d7\n",
        "\n",
        "explain = df[['RM','DIS', 'ZN']].values\n",
        "target = df[['PRICE']].values\n",
        "\n",
        "# ネット上のStratified KfoldやGaussianNBを使用しているものを参考にしたため\n",
        "# 動作するまで手こずった。\n",
        "# StratifiedKfolde:  分類問題でないと使用できない\n",
        "# GaussianNB:  ValueErrorが出て動かなかった\n",
        "# ndarrayがまずいのかと思いtolist()に変えたりしたが、これは結局どちらでも動作する。\n",
        "\n",
        "model = LinearRegression()\n",
        "from sklearn.naive_bayes import GaussianNB\n",
        "\n",
        "kf = KFold(n_splits = 5)\n",
        "# print(target.shape)\n",
        "# print(type(explain))\n",
        "import sklearn\n",
        "scores = cross_validate(model, explain, target, cv=kf, scoring=scoring)\n",
        "\n",
        "# これは評価方法の種類を列挙する\n",
        "# pprint(sorted(sklearn.metrics.SCORERS.keys()))\n",
        "\n",
        "pprint(scores)\n",
        "print(\"MSE: \", scores[\"test_neg_mean_squared_error\"].mean())\n",
        "print(\"MAE: \", scores[\"test_neg_median_absolute_error\"].mean())"
      ],
      "execution_count": 140,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "{'fit_time': array([0.00064301, 0.00052547, 0.00051951, 0.00049567, 0.00047207]),\n",
            " 'score_time': array([0.00067782, 0.00059533, 0.00054741, 0.00055766, 0.00056434]),\n",
            " 'test_neg_mean_squared_error': array([ -10.48618691,  -34.68155751,  -39.92397823, -104.6938281 ,\n",
            "        -72.95736673]),\n",
            " 'test_neg_median_absolute_error': array([-2.18699661, -2.62695139, -4.24303442, -2.67800476, -6.78113431])}\n",
            "MSE:  -52.5485834971779\n",
            "MAE:  -3.7032242990755533\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ECxxyN_UHNOI"
      },
      "source": [
        "### ここからは、ボストン住宅データを線形回帰以外のアルゴリズムで実験的に学習する。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gh8t0oaGdIAg",
        "outputId": "69ca663d-c60a-4327-a09d-34531fe67845"
      },
      "source": [
        "# ElasticNet\n",
        "\n",
        "# サンプルをもとに改変\n",
        "# https://blog.amedama.jp/entry/sklearn-cv-custom-metric\n",
        "\n",
        "import math\n",
        "from sklearn import datasets\n",
        "from sklearn.linear_model import ElasticNet\n",
        "from sklearn.model_selection import KFold\n",
        "from sklearn.model_selection import cross_validate\n",
        "from sklearn.metrics import mean_squared_error\n",
        "from sklearn.metrics import make_scorer\n",
        "\n",
        "\n",
        "def rmse_score(y_true, y_pred):\n",
        "    \"\"\"RMSE (Root Mean Square Error: 平均二乗誤差平方根) を計算する関数\"\"\"\n",
        "    mse = mean_squared_error(y_true, y_pred)\n",
        "    rmse = math.sqrt(mse)\n",
        "    return rmse\n",
        "\n",
        "\n",
        "def main():\n",
        "    # Boston データセットを使った回帰問題\n",
        "    # dataset = datasets.load_boston()\n",
        "    # X, y = dataset.data, dataset.target\n",
        "\n",
        "    # ElasticNet 回帰\n",
        "    reg = ElasticNet(random_state=10)\n",
        "\n",
        "    kf = KFold(n_splits=5, shuffle=True, random_state=10)\n",
        "\n",
        "    score_funcs = {\n",
        "        'rmse': make_scorer(rmse_score),\n",
        "        'mae': 'neg_median_absolute_error'\n",
        "    }\n",
        "\n",
        "    # 出力はこのように平均して出す。\n",
        "    scores = cross_validate(reg, explain, target, cv=kf, scoring=score_funcs)\n",
        "    mean_rmse = scores['test_rmse'].mean()\n",
        "    print('RMSE:', mean_rmse)\n",
        "    mean_mae = scores['test_mae'].mean()\n",
        "    print('MAE:', mean_mae)\n",
        "\n",
        "main()"
      ],
      "execution_count": 141,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "RMSE: 7.335149087760584\n",
            "MAE: -3.5821757778028953\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T951JN9CerY6"
      },
      "source": [
        "# LightGBM\n",
        "param = {\n",
        "        'boosting_type': 'gbdt',\n",
        "        'objective': 'binary',\n",
        "        'max_depth': -1,\n",
        "        'learning_rate': 0.01,        \n",
        "    }\n",
        "fit_params = {\n",
        "    'early_stopping_rounds': 10\n",
        "}\n",
        "\n",
        "# これがClassifierになっているとよく分からないエラーが出て気づきづらいので注意。\n",
        "model = lightgbm.LGBMRegressor(**param)\n",
        "lgbm_explain = lightgbm.Dataset(explain.tolist())\n",
        "lgbm_target = lightgbm.Dataset(target.tolist())"
      ],
      "execution_count": 152,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OEwDb38XqFTY"
      },
      "source": [
        ""
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y1d3NxWCv5rf",
        "outputId": "ff3e4c07-d418-4815-a1bb-6e27c7a37c60"
      },
      "source": [
        "# 誤差関数を定義して使用\n",
        "# RMSE 23、MER 0.9 という結果\n",
        "# さっきの線形回帰よりはよい\n",
        "\n",
        "# データの分割\n",
        "#X = df.drop(['MEDV'],axis=1)\n",
        "#y = df['MEDV']\n",
        "X = df.drop(['PRICE'], axis=1)\n",
        "y = df['PRICE']\n",
        "\n",
        "# trainデータ, testデータへの分割\n",
        "from sklearn.model_selection import train_test_split\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)\n",
        "\n",
        "# Cross Validationによる予測精度の評価\n",
        "from sklearn.model_selection import cross_validate\n",
        "from sklearn.metrics import mean_squared_error, r2_score, make_scorer\n",
        "\n",
        "# 誤差関数の定義\n",
        "def root_mean_squared_error(y_true, y_pred):\n",
        "    return np.sqrt(mean_squared_error(y_true, y_pred))\n",
        "\n",
        "def median_absolute_error_rate(y_true, y_pred):\n",
        "    return np.median(np.absolute(y_true - y_pred) / y_true)\n",
        "\n",
        "# Cross Validationで使う誤差関数のセット\n",
        "scoring = {\"r2\": \"r2\",\n",
        "           \"RMSE\":make_scorer(root_mean_squared_error),\n",
        "           \"MER\":make_scorer(median_absolute_error_rate)}\n",
        "\n",
        "model = lightgbm.LGBMRegressor(**param)\n",
        "\n",
        "# cross_validate\n",
        "scores = cross_validate(model, X_train, y_train, cv = 10, scoring = scoring, return_train_score=False)\n",
        "for key,value in scores.items():\n",
        "    print(\"{}:{:.3g}+/-{:.3g}\".format(key, value.mean(), value.std()))\n",
        "\n",
        "# 結果を格納\n",
        "cv_accuracy_EN = pd.DataFrame(scores)[['test_r2','test_RMSE','test_MER']].mean()\n",
        "\n",
        "# MERの結果が良すぎる"
      ],
      "execution_count": 143,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "fit_time:0.00704+/-0.00138\n",
            "score_time:0.00424+/-0.000608\n",
            "test_r2:-5.97+/-1.47\n",
            "test_RMSE:23.5+/-1.35\n",
            "test_MER:0.953+/-0.00223\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k9cKz-4-quqW",
        "outputId": "8973a994-15b9-430b-922a-41279daf5935"
      },
      "source": [
        "# 線形回帰のときにやった指定方法で実施してみる。\n",
        "\n",
        "# データの分割\n",
        "X = df.drop(['PRICE'], axis=1)\n",
        "y = df['PRICE']\n",
        "\n",
        "# trainデータ, testデータへの分割\n",
        "from sklearn.model_selection import train_test_split\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)\n",
        "\n",
        "# Cross Validationによる予測精度の評価\n",
        "from sklearn.model_selection import cross_validate\n",
        "from sklearn.metrics import mean_squared_error, r2_score, make_scorer\n",
        "\n",
        "scoring = [\n",
        "  \"r2\",\n",
        "  'neg_mean_squared_error',\n",
        "  'neg_median_absolute_error']\n",
        "\n",
        "model = lightgbm.LGBMRegressor(**param)\n",
        "\n",
        "# cross_validate\n",
        "scores = cross_validate(model, X_train, y_train, cv = 10, scoring = scoring, return_train_score=False)\n",
        "for key,value in scores.items():\n",
        "    print(\"{}:{:.3g}+/-{:.3g}\".format(key, value.mean(), value.std()))\n",
        "\n",
        "# 結果を格納\n",
        "cv_accuracy_EN = pd.DataFrame(scores)[['test_r2','test_neg_mean_squared_error','test_neg_median_absolute_error']].mean()\n",
        "\n",
        "print(cv_accuracy_EN['test_neg_mean_squared_error'])\n",
        "np.sqrt(-1 * cv_accuracy_EN['test_neg_mean_squared_error'])\n",
        "\n",
        "np.sqrt(-1 * cv_accuracy_EN['test_neg_median_absolute_error'])\n"
      ],
      "execution_count": 153,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "fit_time:0.00732+/-0.00263\n",
            "score_time:0.00361+/-0.000282\n",
            "test_r2:-5.97+/-1.47\n",
            "test_neg_mean_squared_error:-553+/-63.9\n",
            "test_neg_median_absolute_error:-20.2+/-0.944\n",
            "-552.6385835365853\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4.491102314577124"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 153
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tXFmM-zLEMxh",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "40b976fd-b8ee-41a9-c76b-7877f99b5fa0"
      },
      "source": [
        "cross_validate(model, X_train, y_train, cv = 10, scoring = scoring, return_train_score=False)"
      ],
      "execution_count": 145,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'fit_time': array([0.01201844, 0.00633311, 0.00649858, 0.006392  , 0.00633764,\n",
              "        0.00631905, 0.0062623 , 0.00633526, 0.00647545, 0.00689149]),\n",
              " 'score_time': array([0.00373602, 0.00347638, 0.0035274 , 0.0034709 , 0.00344324,\n",
              "        0.00333667, 0.00337362, 0.00362539, 0.00349236, 0.00331211]),\n",
              " 'test_neg_mean_squared_error': array([-504.97463415, -446.83780488, -593.78804878, -494.68609756,\n",
              "        -554.57425   , -573.93125   , -588.68375   , -693.401     ,\n",
              "        -550.9525    , -524.5565    ]),\n",
              " 'test_neg_median_absolute_error': array([-19.6 , -19.5 , -21.  , -20.5 , -19.9 , -20.4 , -21.  , -20.45,\n",
              "        -17.95, -21.4 ]),\n",
              " 'test_r2': array([-4.77640032, -7.31563689, -5.86937511, -8.12736233, -5.90501176,\n",
              "        -5.16361623, -6.52189481, -4.49242545, -3.49135777, -8.07843869])}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 145
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZWX8q2dtkKFg"
      },
      "source": [
        "# 参考\n",
        "# https://qiita.com/kibinag0/items/1a29db61fcb8c527d952\n",
        "\n",
        "\n",
        "# scikit-learn を用いた交差検証（Cross-validation）と\n",
        "# ハイパーパラメータのチューニング（grid search）\n",
        "# https://qiita.com/tomov3/items/039d4271ed30490edf7b\n",
        "\n"
      ],
      "execution_count": 146,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FafE-_NXKI9g"
      },
      "source": [
        "### 単純な線形回帰モデルを自分で書く\n",
        "\n",
        "$$\n",
        "a = \\frac{cov(x, y)}{s_x} \\\\\n",
        "　\\\\\n",
        "b = \\bar{y} - a・\\bar{x} \\\\\n",
        "　\\\\\n",
        "$$\n",
        "y = ax + b  となる線形回帰\n",
        "　\n",
        "\n",
        "\n",
        "\n",
        ".\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H8qAUOW5oZxn"
      },
      "source": [
        "# 単純な線形回帰の実装\n",
        "\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "\n",
        "def linear(n_size):\n",
        "  # 真のデータを生成する関数\n",
        "  def base_func(x):\n",
        "      return 1.5 * x + 6\n",
        "\n",
        "  # 学習データ生成\n",
        "  def fractuate(y_base):\n",
        "      return y_base + np.random.normal(scale=0.3, size=y_base.shape)\n",
        "\n",
        "  x_train = np.linspace(0, 1, n_size)\n",
        "  y_base = base_func(x_train)\n",
        "  y_train = fractuate(y_base)\n",
        "\n",
        "  #学習\n",
        "  def train(x, y):\n",
        "      cov = np.cov(x, y, ddof=0)\n",
        "      a = cov[0, 1] / cov[0, 0]\n",
        "      b = np.mean(y) - a * np.mean(x)\n",
        "      return cov, a, b\n",
        "\n",
        "  cov, a, b = train(x_train, y_train)\n",
        "\n",
        "  #予測\n",
        "  #xs_new = np.linspace(0, 1, n_sample)\n",
        "  ys_pred = a * x_train + b\n",
        "\n",
        "  #結果の描画\n",
        "  plt.scatter(x_train, y_train, facecolor=\"none\", edgecolor=\"b\", s=50, label=\"training data\")\n",
        "  plt.plot(x_train, y_base, label=\"$1.5 x + 6$\")\n",
        "  plt.plot(x_train, ys_pred, label=f\"prediction (a={a:.4}, b={b:.4}), dat_size{n_size}\")\n",
        "  plt.legend()\n",
        "  plt.show()"
      ],
      "execution_count": 147,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "oEOFhPLaDsLw",
        "outputId": "d091318a-8b7f-4a98-e0e5-61945bfc1e38"
      },
      "source": [
        "# データが増えるにつれて結果は安定する。（真の値に近い線になりやすい）\n",
        "n_size = 10\n",
        "linear(n_size)\n",
        "n_size = 20\n",
        "linear(n_size)\n",
        "n_size = 40\n",
        "linear(n_size)\n",
        "n_size = 60\n",
        "linear(n_size)\n",
        "n_size = 80\n",
        "linear(n_size)\n",
        "n_size = 100\n",
        "linear(n_size)\n",
        "n_size = 120\n",
        "linear(n_size)\n",
        "n_size = 140\n",
        "\n",
        "linear(n_size)"
      ],
      "execution_count": 148,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zW3W5uTAYYch"
      },
      "source": [
        ""
      ],
      "execution_count": 148,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EOxKSEFZ62Ah"
      },
      "source": [
        "### 線形回帰（行列バージョン）を自分で書く\n",
        "\n",
        "$$\n",
        "W = (X^TX)^{-1}X^Ty  \\\\\n",
        "\\hat{y} = X_*W\n",
        "$$"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JfsIaX8BWegt",
        "outputId": "47b8d708-4bd4-41d8-f54b-778fed67dc5b"
      },
      "source": [
        "# 線形回帰（行列バージョン）\n",
        "import numpy as np\n",
        "# 説明変数\n",
        "x = np.array([[1, 1.1, 1.0],\n",
        "              [1, 2.5, 2.3],\n",
        "              [1, 3.5, 3.1],\n",
        "              [1, 3.6, 3.9],\n",
        "              [1, 4.5, 4.9],\n",
        "              [1, 4.5, 4.0],\n",
        "              [1, 5.0, 5.6],\n",
        "              [1, 5.5, 7.0],\n",
        "              [1, 5.6, 6.6],\n",
        "              [1, 6.0, 7.0],\n",
        "              [1, 7.0, 7.9], \n",
        "              [1, 7.8, 6.8],\n",
        "              [1, 8.2, 8.5],\n",
        "              [1, 8.5, 8.9],\n",
        "              [1, 9.0, 9.9],\n",
        "              [1, 9.5, 9.5]])\n",
        "# 教師データ\n",
        "y = np.array([[3.1], [4.5], [4.9], [5.5], [6.3], [6.6], [7.5], [7.6], [7.9], [8.0], [9.0], [9.9], [10.1], [10.5], [11.2], [12.1]])\n",
        "# print(y)\n",
        "# 新規説明変数\n",
        "xstar = np.array(([1, 5, 6]))   # 想定7くらい？\n",
        "\n",
        "# 予測計算(最小二乗法)\n",
        "xx = x.T @ x\n",
        "xxinv = np.linalg.inv(xx)\n",
        "w = xxinv @ x.T @ y\n",
        "yhat = xstar @ w\n",
        "print(yhat)\n",
        "# だいたい想定どおり(7.06551346)"
      ],
      "execution_count": 149,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[7.06551346]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O2lzISjSRKAM"
      },
      "source": [
        "# ロジスティック回帰\n",
        "\n",
        "教材のnp_logistic_regression.ipynbを参考に。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CPzpl0q8VLiA"
      },
      "source": [
        "%matplotlib inline\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 246,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4tjFwNqGVOAM"
      },
      "source": [
        "n_sample = 300\n",
        "harf_n_sample = int(n_sample / 2) # n_sampleの半分だが、int型にしないと落ちる。\n",
        "var = .2\n",
        "\n",
        "def gen_data(n_sample, harf_n_sample):\n",
        "    x0 = np.random.normal(size=n_sample).reshape(-1, 2) - 1.\n",
        "    x1 = np.random.normal(size=n_sample).reshape(-1, 2) + 1.\n",
        "    # -1したものと+1したものを結合\n",
        "    x_train = np.concatenate([x0, x1])\n",
        "    # print(x_train)\n",
        "    # 前半は0、後半は1の教師ラベルを作成\n",
        "    y_train = np.concatenate([np.zeros(harf_n_sample), np.ones(harf_n_sample)]).astype(np.int)\n",
        "    return x_train, y_train\n",
        "\n",
        "def plt_data(x_train, y_train):\n",
        "    plt.scatter(x_train[:, 0], x_train[:, 1], c=y_train, facecolor=\"none\", edgecolor=\"b\", s=50, label=\"training data\")\n",
        "    plt.legend()"
      ],
      "execution_count": 247,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "py0guBi-VTz6",
        "outputId": "85e88747-64a4-4f3a-d83a-64b3844be6f9"
      },
      "source": [
        "#データ作成\n",
        "x_train, y_train = gen_data(n_sample, harf_n_sample)\n",
        "#データ表示\n",
        "plt_data(x_train, y_train)"
      ],
      "execution_count": 249,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "03gysWD6Vakf"
      },
      "source": [
        "識別モデルとして$p(y=1 | \\boldsymbol{x}; \\boldsymbol{w}) = \\sigma (\\boldsymbol{w}^{\\mathrm{T}} \\boldsymbol{x})$を用いる。\n",
        "\n",
        "ただし、$\\sigma(\\cdot)$はシグモイド関数であり、$\\sigma(h) = \\frac{1}{1 + \\exp{(-h)}}$で定義される。\n",
        "\n",
        "また、陽には書かないが、$\\boldsymbol{x}$には定数項のための$1$という要素があることを仮定する。"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "55wSSFQCVxBA"
      },
      "source": [
        "訓練データ$X = [\\boldsymbol{x}_{1}, \\boldsymbol{x}_{2}, ..., \\boldsymbol{x}_{n}]^{\\mathrm{T}}, \\boldsymbol{y} = [y_{1}, y_{2}, ..., y_{n}]^{\\mathrm{T}} (y_{i} = \\{0, 1\\})$に対して尤度関数$L$は以下のように書ける。\n",
        "\n",
        "$L(\\boldsymbol{w}) = \\prod_{i=1}^{n} p(y_{i}=1 | \\boldsymbol{x}_{i}; \\boldsymbol{w})^{y_{i}} (1 - p(y_{i}=1 | \\boldsymbol{x}_{i}; \\boldsymbol{w}))^{1 - y_{i}}$\n",
        "\n",
        "負の対数尤度関数は\n",
        "\n",
        "$- \\log{L(\\boldsymbol{w})} = - \\sum_{i=1}^{n} \\left[ y_{i} \\log{p(y_{i}=1 | \\boldsymbol{x}_{i}; \\boldsymbol{w})} + (1 - y_{i}) \\log{(1 - p(y_{i}=1 | \\boldsymbol{x}_{i}; \\boldsymbol{w}))} \\right]$\n",
        "\n",
        "のように書ける。 これを最小化する$\\boldsymbol{w}$を求める。\n",
        "\n",
        "$\\frac{d \\sigma(h)}{d h} = \\sigma(h)(1 - \\sigma(h))$と書けることを考慮し、負の対数尤度関数を$\\boldsymbol{w}$で偏微分すると、\n",
        "\n",
        "\\begin{eqnarray}\n",
        "\\frac{\\partial }{\\partial \\boldsymbol{w}} (-\\log{L(\\boldsymbol{w})}) &=& -\\sum_{i=1}^{n} \\left[ y_{i} (1 - \\sigma(\\boldsymbol{w}^{\\mathrm{T}} \\boldsymbol{x}_{i})) - (1 - y_{i}) \\sigma(\\boldsymbol{w}^{\\mathrm{T}} \\boldsymbol{x}_{i}) \\right] \\boldsymbol{x}_{i}  \\\\\n",
        "&=& \\sum_{i=1}^{n} \\left( \\sigma(\\boldsymbol{w}^{\\mathrm{T}} \\boldsymbol{x}_{i}) - y_{i} ) \\right) \\boldsymbol{x}_{i}\n",
        "\\end{eqnarray}\n",
        "\n",
        "この式が$0$となる$\\boldsymbol{w}$は解析的に求められないので、今回は$-\\log{L(\\boldsymbol{w})}$の最小化問題を最急降下法を用いて解く。\n",
        "\n",
        "最急降下法では学習率を$\\eta$とすると、以下の式で$\\boldsymbol{w}$を更新する。\n",
        "\n",
        "$\\boldsymbol{w} \\leftarrow \\boldsymbol{w} - \\eta \\frac{\\partial }{\\partial \\boldsymbol{w}} (-\\log{L(\\boldsymbol{w})})$"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "04hWTDQGV3rm"
      },
      "source": [
        "# w0は定数項なので、入力値のx0として1固定の列が必要なので追加する。\n",
        "def add_one(x):\n",
        "  result = np.concatenate([np.ones(len(x))[:, None], x], axis=1)\n",
        "  return result"
      ],
      "execution_count": 250,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Jllx0SNDV6lT"
      },
      "source": [
        "def sigmoid(x):\n",
        "    return 1 / (1 + np.exp(-x))\n",
        "\n",
        "def sgd(X_train, y_train, max_iter, eta):\n",
        "    w = np.zeros(X_train.shape[1])\n",
        "    for _ in range(max_iter):\n",
        "        w_prev = np.copy(w)\n",
        "        sigma = sigmoid(np.dot(X_train, w))\n",
        "        grad = np.dot(X_train.T, (sigma - y_train))\n",
        "        w -= eta * grad\n",
        "        if np.allclose(w, w_prev):\n",
        "            # max_iter到達前でも、更新前後でwが変化しないようなら終了。\n",
        "            return w\n",
        "    return w"
      ],
      "execution_count": 251,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fYZ48HiCV8O6"
      },
      "source": [
        "X_train = add_one(x_train)\n",
        "max_iter=100\n",
        "eta = 0.01\n",
        "w = sgd(X_train, y_train, max_iter, eta)"
      ],
      "execution_count": 252,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pgXdNZXoV_ay",
        "outputId": "cee15e2f-e31f-4166-aa94-a32967ee093a"
      },
      "source": [
        "print(w)"
      ],
      "execution_count": 253,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[-0.08766741  2.43918466  2.09326836]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6ef5vLdnbp6D"
      },
      "source": [
        "## 予測\n",
        "入力に対して、$y=1$である確率を出力する。よって\n",
        "\n",
        "$p(y=1 | \\boldsymbol{x}; \\boldsymbol{w}) = \\sigma (\\boldsymbol{w}^{\\mathrm{T}} \\boldsymbol{x})$の値が\n",
        "\n",
        "$0.5$より大きければ1に、小さければ0に分類する。"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8vgJtxaWbv31"
      },
      "source": [
        "# -5～5まで100分割の格子点を作成している。\n",
        "xx0, xx1 = np.meshgrid(np.linspace(-5, 5, 100), np.linspace(-5, 5, 100))\n",
        "xx = np.array([xx0, xx1]).reshape(2, -1).T"
      ],
      "execution_count": 254,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LiEWCVC3bxya",
        "outputId": "cec3a581-7ef3-45ed-edeb-f5f4d0fc3e82"
      },
      "source": [
        "X_test = add_one(xx)\n",
        "proba = sigmoid(np.dot(X_test, w))\n",
        "y_pred = (proba > 0.5).astype(np.int)\n",
        "print(y_pred)\n",
        "print(len(y_pred)) # 100*100なので10000件"
      ],
      "execution_count": 255,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[0 0 0 ... 1 1 1]\n",
            "10000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "4_ElWtVebzZ5",
        "outputId": "271bfdd3-45fb-43d8-cad3-5d50b1f94aae"
      },
      "source": [
        "plt.scatter(x_train[:, 0], x_train[:, 1], c=y_train)\n",
        "plt.contourf(xx0, xx1, proba.reshape(100, 100), alpha=0.2, levels=np.linspace(0, 1, 3))\n",
        "print(w)"
      ],
      "execution_count": 256,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[-0.08766741  2.43918466  2.09326836]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_lpVj5Calj7n",
        "outputId": "056120d1-a11a-4357-e6f2-d0f72fe12950"
      },
      "source": [
        "x_test = [[1, 3, 1.5]]\n",
        "predict_single = sigmoid(np.dot(x_test, w))\n",
        "print(predict_single)\n",
        "\n",
        "x_test = [[1, -1, -1.5]]\n",
        "predict_single = sigmoid(np.dot(x_test, w))\n",
        "print(predict_single)\n",
        "\n",
        "x_test = [[1, -0.1, -0.2]]\n",
        "predict_single = sigmoid(np.dot(x_test, w))\n",
        "print(predict_single)\n",
        "\n",
        "x_test = [[1, -0.1, 0.2]]\n",
        "predict_single = sigmoid(np.dot(x_test, w))\n",
        "print(predict_single)"
      ],
      "execution_count": 265,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[0.99996864]\n",
            "[0.00344715]\n",
            "[0.32076911]\n",
            "[0.52175321]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 537
        },
        "id": "nJ2lMH4pb19r",
        "outputId": "c4298194-74c9-418d-9f38-f725aed691f3"
      },
      "source": [
        "\n",
        "# scikit learn との比較\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "model=LogisticRegression(fit_intercept=True)\n",
        "model.fit(x_train, y_train)\n",
        "proba = model.predict_proba(xx)\n",
        "y_pred = (proba > 0.5).astype(np.int)\n",
        "plt.scatter(x_train[:, 0], x_train[:, 1], c=y_train)\n",
        "plt.contourf(xx0, xx1, proba[:, 0].reshape(100, 100), alpha=0.2, levels=np.linspace(0, 1, 3))\n",
        "import pprint\n",
        "pprint.pprint(model.get_params())\n",
        "pprint.pprint(model.coef_)"
      ],
      "execution_count": 240,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "{'C': 1.0,\n",
            " 'class_weight': None,\n",
            " 'dual': False,\n",
            " 'fit_intercept': True,\n",
            " 'intercept_scaling': 1,\n",
            " 'l1_ratio': None,\n",
            " 'max_iter': 100,\n",
            " 'multi_class': 'auto',\n",
            " 'n_jobs': None,\n",
            " 'penalty': 'l2',\n",
            " 'random_state': None,\n",
            " 'solver': 'lbfgs',\n",
            " 'tol': 0.0001,\n",
            " 'verbose': 0,\n",
            " 'warm_start': False}\n",
            "array([[2.15008286, 2.16395346]])\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "al9lT2zWRLCq"
      },
      "source": [
        ""
      ],
      "execution_count": 150,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ebRDKmxkRDrk"
      },
      "source": [
        ""
      ],
      "execution_count": 150,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QtUSB2axRG40"
      },
      "source": [
        ""
      ],
      "execution_count": 265,
      "outputs": []
    }
  ]
}