33.Random_Forest_Regression.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "33.Random_Forest_Regression.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 990
        },
        "id": "M83cKR2MtPZ3",
        "outputId": "e9a7a7a5-e6e9-4cf6-9bd0-a70e67141180"
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import pandas as pd\n",
        "datas = pd.read_csv('LinearData.csv')\n",
        "datas"
      ],
      "execution_count": 1,
      "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>X</th>\n",
              "      <th>Y</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>953</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>2068</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>2871</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>3972</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>5240</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>6</td>\n",
              "      <td>5610</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>7</td>\n",
              "      <td>7196</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>8</td>\n",
              "      <td>7936</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>9</td>\n",
              "      <td>8577</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>10</td>\n",
              "      <td>10950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>11</td>\n",
              "      <td>11077</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>12</td>\n",
              "      <td>12468</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>13</td>\n",
              "      <td>13780</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>14</td>\n",
              "      <td>13888</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>15</td>\n",
              "      <td>14325</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>16</td>\n",
              "      <td>14496</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>17</td>\n",
              "      <td>16116</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>18</td>\n",
              "      <td>17064</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>19</td>\n",
              "      <td>20387</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>20</td>\n",
              "      <td>18620</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>21</td>\n",
              "      <td>20517</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>22</td>\n",
              "      <td>22264</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>23</td>\n",
              "      <td>22770</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>24</td>\n",
              "      <td>25344</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>25</td>\n",
              "      <td>23450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>26</td>\n",
              "      <td>28522</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>27</td>\n",
              "      <td>25920</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>28</td>\n",
              "      <td>30072</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>29</td>\n",
              "      <td>31813</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>30</td>\n",
              "      <td>32370</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     X      Y\n",
              "0    1    953\n",
              "1    2   2068\n",
              "2    3   2871\n",
              "3    4   3972\n",
              "4    5   5240\n",
              "5    6   5610\n",
              "6    7   7196\n",
              "7    8   7936\n",
              "8    9   8577\n",
              "9   10  10950\n",
              "10  11  11077\n",
              "11  12  12468\n",
              "12  13  13780\n",
              "13  14  13888\n",
              "14  15  14325\n",
              "15  16  14496\n",
              "16  17  16116\n",
              "17  18  17064\n",
              "18  19  20387\n",
              "19  20  18620\n",
              "20  21  20517\n",
              "21  22  22264\n",
              "22  23  22770\n",
              "23  24  25344\n",
              "24  25  23450\n",
              "25  26  28522\n",
              "26  27  25920\n",
              "27  28  30072\n",
              "28  29  31813\n",
              "29  30  32370"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ipTJm_kbwnOJ"
      },
      "source": [
        "X = datas.iloc[:, :-1].values\n",
        "y = datas.iloc[:, -1].values"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4_1YE6Y-wr6Z",
        "outputId": "981a91df-4a28-40b0-b6bc-2cd34ce51be1"
      },
      "source": [
        "X"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[ 1],\n",
              "       [ 2],\n",
              "       [ 3],\n",
              "       [ 4],\n",
              "       [ 5],\n",
              "       [ 6],\n",
              "       [ 7],\n",
              "       [ 8],\n",
              "       [ 9],\n",
              "       [10],\n",
              "       [11],\n",
              "       [12],\n",
              "       [13],\n",
              "       [14],\n",
              "       [15],\n",
              "       [16],\n",
              "       [17],\n",
              "       [18],\n",
              "       [19],\n",
              "       [20],\n",
              "       [21],\n",
              "       [22],\n",
              "       [23],\n",
              "       [24],\n",
              "       [25],\n",
              "       [26],\n",
              "       [27],\n",
              "       [28],\n",
              "       [29],\n",
              "       [30]])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "A0a9m2DewwWS",
        "outputId": "70e1e1c0-d955-45ce-ea0e-0b009426f9a6"
      },
      "source": [
        "y"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([  953,  2068,  2871,  3972,  5240,  5610,  7196,  7936,  8577,\n",
              "       10950, 11077, 12468, 13780, 13888, 14325, 14496, 16116, 17064,\n",
              "       20387, 18620, 20517, 22264, 22770, 25344, 23450, 28522, 25920,\n",
              "       30072, 31813, 32370])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4GBhRFq6xC7d"
      },
      "source": [
        "from sklearn.ensemble import RandomForestRegressor\n",
        "from sklearn.datasets import make_regression"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cQq7ZxVRwwyj",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "588cddd3-f44f-40e5-c41f-77fdf4119a74"
      },
      "source": [
        "X, y = make_regression(n_features=4, n_informative=2, random_state=0, shuffle=False)\n",
        "clf = RandomForestRegressor(max_depth=2, random_state=0)\n",
        "clf.fit(X, y)"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',\n",
              "                      max_depth=2, max_features='auto', max_leaf_nodes=None,\n",
              "                      max_samples=None, min_impurity_decrease=0.0,\n",
              "                      min_impurity_split=None, min_samples_leaf=1,\n",
              "                      min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
              "                      n_estimators=100, n_jobs=None, oob_score=False,\n",
              "                      random_state=0, verbose=0, warm_start=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7vZB-6cvw2G8",
        "outputId": "a266f89c-efab-4621-927a-e9f6bf2b3f26"
      },
      "source": [
        "clf.predict(X)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 29.61901976, -11.02118762,  14.62139516,   9.80192217,\n",
              "         0.49423187,   6.4746029 , -20.32548943,  60.07190209,\n",
              "       -43.63959083,  57.75151636, -42.08374658, -29.21899598,\n",
              "       -26.87520041, -35.5562676 ,  13.00221212, -30.27667951,\n",
              "       -15.30998867, -15.07085954, -14.3798838 , -32.77944477,\n",
              "        17.75011607,  60.75235947,  32.39695083,  34.89481082,\n",
              "        41.82746706, -15.81990323,  38.35651914,  61.7155606 ,\n",
              "        39.8305456 ,   0.21346688, -18.52788719, -15.07085954,\n",
              "        20.03487674, -15.07085954,  -2.64590913,   6.29322227,\n",
              "        53.24909298, -31.72005631, -32.77944477, -11.61409181,\n",
              "        39.8305456 ,  15.42240915,  20.19566646, -11.02118762,\n",
              "       -32.77944477, -39.77817286, -27.75309607,  39.8305456 ,\n",
              "       -29.94592506,  28.81337665, -27.04219045, -27.75309607,\n",
              "        -2.98099169, -10.23166651,  12.18025706, -30.52121188,\n",
              "       -16.64428086, -27.76253299,  12.5021081 , -21.88133368,\n",
              "       -29.93933852, -40.90011089, -43.63959083, -15.69533437,\n",
              "       -41.08038876, -32.77944477,  -6.20818992,  -8.66506067,\n",
              "        28.59436108,  -2.30572014,  32.89788936,  17.79461147,\n",
              "        47.23059518, -11.02118762,  17.79461147,  37.70653973,\n",
              "       -11.89244448,  -0.85142976, -32.77944477, -23.94425492,\n",
              "       -32.77944477, -30.52121188,  21.83863007, -15.04016346,\n",
              "         5.71482632,  -9.18394963, -28.51295606,  15.39850958,\n",
              "       -11.02118762, -32.40402309,  -0.85142976,   5.00684534,\n",
              "       -31.66890516,  -7.69516062, -27.75309607,   0.42991065,\n",
              "       -35.78873883,  15.97409317, -42.33737493,  49.89924108])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8SOcQ_b1xUKH"
      },
      "source": [
        ""
      ],
      "execution_count": 7,
      "outputs": []
    }
  ]
}