DECISION_TREE.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyNwwUmoHYl0JA8bND1/eNt7",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Swastik200/30DaysOfDSA/blob/main/DECISION_TREE.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "RNHDl3MbVJrv"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import random\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AzOq7QRLVZoZ",
        "outputId": "30b270a7-069e-4f2d-c422-1220d1c0293f"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import mean_squared_error, r2_score,mean_absolute_error\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import StandardScaler,MinMaxScaler"
      ],
      "metadata": {
        "id": "MwMvJ6qJVpaJ"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.ensemble import ExtraTreesRegressor"
      ],
      "metadata": {
        "id": "IOlPhxaWVqaR"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!cp \"/content/drive/MyDrive/CMAPSS.zip\" \"/content\"\n",
        "!unzip CMAPSS.zip"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EWimGU7sV1YM",
        "outputId": "77bf6584-2a68-45a9-a689-65c260665c9c"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  CMAPSS.zip\n",
            "  inflating: CMAPSS/readme.txt       \n",
            "  inflating: CMAPSS/RUL_FD001.txt    \n",
            "  inflating: CMAPSS/RUL_FD002.txt    \n",
            "  inflating: CMAPSS/RUL_FD003.txt    \n",
            "  inflating: CMAPSS/RUL_FD004.txt    \n",
            "  inflating: CMAPSS/test_FD001.txt   \n",
            "  inflating: CMAPSS/test_FD002.txt   \n",
            "  inflating: CMAPSS/test_FD003.txt   \n",
            "  inflating: CMAPSS/test_FD004.txt   \n",
            "  inflating: CMAPSS/train_FD001.txt  \n",
            "  inflating: CMAPSS/train_FD002.txt  \n",
            "  inflating: CMAPSS/train_FD003.txt  \n",
            "  inflating: CMAPSS/train_FD004.txt  \n",
            "  inflating: CMAPSS/x.txt            \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "index_names = ['unit_number', 'time_cycles']\n",
        "setting_names = ['setting_1', 'setting_2', 'setting_3']\n",
        "sensor_names = ['sensor_{}'.format(i) for i in range(1,22)]\n",
        "col_names = index_names + setting_names + sensor_names"
      ],
      "metadata": {
        "id": "-JhVyeLNV4jF"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "path = '/content/CMAPSS/'\n",
        "df_train = pd.read_csv(path+'train_FD001.txt',sep='\\s+',header=None,index_col=False,names=col_names) #\\s表示以空白為間隔\n",
        "df_test = pd.read_csv(path+'test_FD001.txt',sep='\\s+',header=None,index_col=False,names=col_names)\n",
        "y_test = pd.read_csv(path+'RUL_FD001.txt',sep='\\s+',header=None,index_col=False,names=['RUL'])\n",
        "y_test.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XmoYzV4TV9po",
        "outputId": "5834bfa1-8c65-44f3-ea46-485313dd7c5f"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(100, 1)"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train = df_train.copy()\n",
        "test = df_test.copy()\n",
        "display(train)\n",
        "display(test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 850
        },
        "id": "6m0_8vDoWC4s",
        "outputId": "4bed64e7-2d28-43b0-af60-29f78f3df17a"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "       unit_number  time_cycles  setting_1  setting_2  setting_3  sensor_1  \\\n",
              "0                1            1    -0.0007    -0.0004      100.0    518.67   \n",
              "1                1            2     0.0019    -0.0003      100.0    518.67   \n",
              "2                1            3    -0.0043     0.0003      100.0    518.67   \n",
              "3                1            4     0.0007     0.0000      100.0    518.67   \n",
              "4                1            5    -0.0019    -0.0002      100.0    518.67   \n",
              "...            ...          ...        ...        ...        ...       ...   \n",
              "20626          100          196    -0.0004    -0.0003      100.0    518.67   \n",
              "20627          100          197    -0.0016    -0.0005      100.0    518.67   \n",
              "20628          100          198     0.0004     0.0000      100.0    518.67   \n",
              "20629          100          199    -0.0011     0.0003      100.0    518.67   \n",
              "20630          100          200    -0.0032    -0.0005      100.0    518.67   \n",
              "\n",
              "       sensor_2  sensor_3  sensor_4  sensor_5  ...  sensor_12  sensor_13  \\\n",
              "0        641.82   1589.70   1400.60     14.62  ...     521.66    2388.02   \n",
              "1        642.15   1591.82   1403.14     14.62  ...     522.28    2388.07   \n",
              "2        642.35   1587.99   1404.20     14.62  ...     522.42    2388.03   \n",
              "3        642.35   1582.79   1401.87     14.62  ...     522.86    2388.08   \n",
              "4        642.37   1582.85   1406.22     14.62  ...     522.19    2388.04   \n",
              "...         ...       ...       ...       ...  ...        ...        ...   \n",
              "20626    643.49   1597.98   1428.63     14.62  ...     519.49    2388.26   \n",
              "20627    643.54   1604.50   1433.58     14.62  ...     519.68    2388.22   \n",
              "20628    643.42   1602.46   1428.18     14.62  ...     520.01    2388.24   \n",
              "20629    643.23   1605.26   1426.53     14.62  ...     519.67    2388.23   \n",
              "20630    643.85   1600.38   1432.14     14.62  ...     519.30    2388.26   \n",
              "\n",
              "       sensor_14  sensor_15  sensor_16  sensor_17  sensor_18  sensor_19  \\\n",
              "0        8138.62     8.4195       0.03        392       2388      100.0   \n",
              "1        8131.49     8.4318       0.03        392       2388      100.0   \n",
              "2        8133.23     8.4178       0.03        390       2388      100.0   \n",
              "3        8133.83     8.3682       0.03        392       2388      100.0   \n",
              "4        8133.80     8.4294       0.03        393       2388      100.0   \n",
              "...          ...        ...        ...        ...        ...        ...   \n",
              "20626    8137.60     8.4956       0.03        397       2388      100.0   \n",
              "20627    8136.50     8.5139       0.03        395       2388      100.0   \n",
              "20628    8141.05     8.5646       0.03        398       2388      100.0   \n",
              "20629    8139.29     8.5389       0.03        395       2388      100.0   \n",
              "20630    8137.33     8.5036       0.03        396       2388      100.0   \n",
              "\n",
              "       sensor_20  sensor_21  \n",
              "0          39.06    23.4190  \n",
              "1          39.00    23.4236  \n",
              "2          38.95    23.3442  \n",
              "3          38.88    23.3739  \n",
              "4          38.90    23.4044  \n",
              "...          ...        ...  \n",
              "20626      38.49    22.9735  \n",
              "20627      38.30    23.1594  \n",
              "20628      38.44    22.9333  \n",
              "20629      38.29    23.0640  \n",
              "20630      38.37    23.0522  \n",
              "\n",
              "[20631 rows x 26 columns]"
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>unit_number</th>\n",
              "      <th>time_cycles</th>\n",
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              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>641.82</td>\n",
              "      <td>1589.70</td>\n",
              "      <td>1400.60</td>\n",
              "      <td>14.62</td>\n",
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              "      <td>521.66</td>\n",
              "      <td>2388.02</td>\n",
              "      <td>8138.62</td>\n",
              "      <td>8.4195</td>\n",
              "      <td>0.03</td>\n",
              "      <td>392</td>\n",
              "      <td>2388</td>\n",
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              "      <td>39.06</td>\n",
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              "      <td>0.0019</td>\n",
              "      <td>-0.0003</td>\n",
              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>642.15</td>\n",
              "      <td>1591.82</td>\n",
              "      <td>1403.14</td>\n",
              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>522.28</td>\n",
              "      <td>2388.07</td>\n",
              "      <td>8131.49</td>\n",
              "      <td>8.4318</td>\n",
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              "      <td>-0.0043</td>\n",
              "      <td>0.0003</td>\n",
              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>642.35</td>\n",
              "      <td>1587.99</td>\n",
              "      <td>1404.20</td>\n",
              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>522.42</td>\n",
              "      <td>2388.03</td>\n",
              "      <td>8133.23</td>\n",
              "      <td>8.4178</td>\n",
              "      <td>0.03</td>\n",
              "      <td>390</td>\n",
              "      <td>2388</td>\n",
              "      <td>100.0</td>\n",
              "      <td>38.95</td>\n",
              "      <td>23.3442</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
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              "      <td>0.0000</td>\n",
              "      <td>100.0</td>\n",
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              "      <td>642.35</td>\n",
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              "      <td>522.86</td>\n",
              "      <td>2388.08</td>\n",
              "      <td>8133.83</td>\n",
              "      <td>8.3682</td>\n",
              "      <td>0.03</td>\n",
              "      <td>392</td>\n",
              "      <td>2388</td>\n",
              "      <td>100.0</td>\n",
              "      <td>38.88</td>\n",
              "      <td>23.3739</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>-0.0019</td>\n",
              "      <td>-0.0002</td>\n",
              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>642.37</td>\n",
              "      <td>1582.85</td>\n",
              "      <td>1406.22</td>\n",
              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>522.19</td>\n",
              "      <td>2388.04</td>\n",
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              "      <td>8.4294</td>\n",
              "      <td>0.03</td>\n",
              "      <td>393</td>\n",
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              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>519.30</td>\n",
              "      <td>2388.26</td>\n",
              "      <td>8137.33</td>\n",
              "      <td>8.5036</td>\n",
              "      <td>0.03</td>\n",
              "      <td>396</td>\n",
              "      <td>2388</td>\n",
              "      <td>100.0</td>\n",
              "      <td>38.37</td>\n",
              "      <td>23.0522</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>20631 rows × 26 columns</p>\n",
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            "text/plain": [
              "       unit_number  time_cycles  setting_1  setting_2  setting_3  sensor_1  \\\n",
              "0                1            1     0.0023     0.0003      100.0    518.67   \n",
              "1                1            2    -0.0027    -0.0003      100.0    518.67   \n",
              "2                1            3     0.0003     0.0001      100.0    518.67   \n",
              "3                1            4     0.0042     0.0000      100.0    518.67   \n",
              "4                1            5     0.0014     0.0000      100.0    518.67   \n",
              "...            ...          ...        ...        ...        ...       ...   \n",
              "13091          100          194     0.0049     0.0000      100.0    518.67   \n",
              "13092          100          195    -0.0011    -0.0001      100.0    518.67   \n",
              "13093          100          196    -0.0006    -0.0003      100.0    518.67   \n",
              "13094          100          197    -0.0038     0.0001      100.0    518.67   \n",
              "13095          100          198     0.0013     0.0003      100.0    518.67   \n",
              "\n",
              "       sensor_2  sensor_3  sensor_4  sensor_5  ...  sensor_12  sensor_13  \\\n",
              "0        643.02   1585.29   1398.21     14.62  ...     521.72    2388.03   \n",
              "1        641.71   1588.45   1395.42     14.62  ...     522.16    2388.06   \n",
              "2        642.46   1586.94   1401.34     14.62  ...     521.97    2388.03   \n",
              "3        642.44   1584.12   1406.42     14.62  ...     521.38    2388.05   \n",
              "4        642.51   1587.19   1401.92     14.62  ...     522.15    2388.03   \n",
              "...         ...       ...       ...       ...  ...        ...        ...   \n",
              "13091    643.24   1599.45   1415.79     14.62  ...     520.69    2388.00   \n",
              "13092    643.22   1595.69   1422.05     14.62  ...     521.05    2388.09   \n",
              "13093    643.44   1593.15   1406.82     14.62  ...     521.18    2388.04   \n",
              "13094    643.26   1594.99   1419.36     14.62  ...     521.33    2388.08   \n",
              "13095    642.95   1601.62   1424.99     14.62  ...     521.07    2388.05   \n",
              "\n",
              "       sensor_14  sensor_15  sensor_16  sensor_17  sensor_18  sensor_19  \\\n",
              "0        8125.55     8.4052       0.03        392       2388      100.0   \n",
              "1        8139.62     8.3803       0.03        393       2388      100.0   \n",
              "2        8130.10     8.4441       0.03        393       2388      100.0   \n",
              "3        8132.90     8.3917       0.03        391       2388      100.0   \n",
              "4        8129.54     8.4031       0.03        390       2388      100.0   \n",
              "...          ...        ...        ...        ...        ...        ...   \n",
              "13091    8213.28     8.4715       0.03        394       2388      100.0   \n",
              "13092    8210.85     8.4512       0.03        395       2388      100.0   \n",
              "13093    8217.24     8.4569       0.03        395       2388      100.0   \n",
              "13094    8220.48     8.4711       0.03        395       2388      100.0   \n",
              "13095    8214.64     8.4903       0.03        396       2388      100.0   \n",
              "\n",
              "       sensor_20  sensor_21  \n",
              "0          38.86    23.3735  \n",
              "1          39.02    23.3916  \n",
              "2          39.08    23.4166  \n",
              "3          39.00    23.3737  \n",
              "4          38.99    23.4130  \n",
              "...          ...        ...  \n",
              "13091      38.65    23.1974  \n",
              "13092      38.57    23.2771  \n",
              "13093      38.62    23.2051  \n",
              "13094      38.66    23.2699  \n",
              "13095      38.70    23.1855  \n",
              "\n",
              "[13096 rows x 26 columns]"
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              "      <td>1395.42</td>\n",
              "      <td>14.62</td>\n",
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              "      <td>14.62</td>\n",
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              "      <td>8130.10</td>\n",
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              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>642.44</td>\n",
              "      <td>1584.12</td>\n",
              "      <td>1406.42</td>\n",
              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>521.38</td>\n",
              "      <td>2388.05</td>\n",
              "      <td>8132.90</td>\n",
              "      <td>8.3917</td>\n",
              "      <td>0.03</td>\n",
              "      <td>391</td>\n",
              "      <td>2388</td>\n",
              "      <td>100.0</td>\n",
              "      <td>39.00</td>\n",
              "      <td>23.3737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>0.0014</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>642.51</td>\n",
              "      <td>1587.19</td>\n",
              "      <td>1401.92</td>\n",
              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>522.15</td>\n",
              "      <td>2388.03</td>\n",
              "      <td>8129.54</td>\n",
              "      <td>8.4031</td>\n",
              "      <td>0.03</td>\n",
              "      <td>390</td>\n",
              "      <td>2388</td>\n",
              "      <td>100.0</td>\n",
              "      <td>38.99</td>\n",
              "      <td>23.4130</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",
              "      <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>13091</th>\n",
              "      <td>100</td>\n",
              "      <td>194</td>\n",
              "      <td>0.0049</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>643.24</td>\n",
              "      <td>1599.45</td>\n",
              "      <td>1415.79</td>\n",
              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>520.69</td>\n",
              "      <td>2388.00</td>\n",
              "      <td>8213.28</td>\n",
              "      <td>8.4715</td>\n",
              "      <td>0.03</td>\n",
              "      <td>394</td>\n",
              "      <td>2388</td>\n",
              "      <td>100.0</td>\n",
              "      <td>38.65</td>\n",
              "      <td>23.1974</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13092</th>\n",
              "      <td>100</td>\n",
              "      <td>195</td>\n",
              "      <td>-0.0011</td>\n",
              "      <td>-0.0001</td>\n",
              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>643.22</td>\n",
              "      <td>1595.69</td>\n",
              "      <td>1422.05</td>\n",
              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>521.05</td>\n",
              "      <td>2388.09</td>\n",
              "      <td>8210.85</td>\n",
              "      <td>8.4512</td>\n",
              "      <td>0.03</td>\n",
              "      <td>395</td>\n",
              "      <td>2388</td>\n",
              "      <td>100.0</td>\n",
              "      <td>38.57</td>\n",
              "      <td>23.2771</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13093</th>\n",
              "      <td>100</td>\n",
              "      <td>196</td>\n",
              "      <td>-0.0006</td>\n",
              "      <td>-0.0003</td>\n",
              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>643.44</td>\n",
              "      <td>1593.15</td>\n",
              "      <td>1406.82</td>\n",
              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>521.18</td>\n",
              "      <td>2388.04</td>\n",
              "      <td>8217.24</td>\n",
              "      <td>8.4569</td>\n",
              "      <td>0.03</td>\n",
              "      <td>395</td>\n",
              "      <td>2388</td>\n",
              "      <td>100.0</td>\n",
              "      <td>38.62</td>\n",
              "      <td>23.2051</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13094</th>\n",
              "      <td>100</td>\n",
              "      <td>197</td>\n",
              "      <td>-0.0038</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>643.26</td>\n",
              "      <td>1594.99</td>\n",
              "      <td>1419.36</td>\n",
              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>521.33</td>\n",
              "      <td>2388.08</td>\n",
              "      <td>8220.48</td>\n",
              "      <td>8.4711</td>\n",
              "      <td>0.03</td>\n",
              "      <td>395</td>\n",
              "      <td>2388</td>\n",
              "      <td>100.0</td>\n",
              "      <td>38.66</td>\n",
              "      <td>23.2699</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13095</th>\n",
              "      <td>100</td>\n",
              "      <td>198</td>\n",
              "      <td>0.0013</td>\n",
              "      <td>0.0003</td>\n",
              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>642.95</td>\n",
              "      <td>1601.62</td>\n",
              "      <td>1424.99</td>\n",
              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>521.07</td>\n",
              "      <td>2388.05</td>\n",
              "      <td>8214.64</td>\n",
              "      <td>8.4903</td>\n",
              "      <td>0.03</td>\n",
              "      <td>396</td>\n",
              "      <td>2388</td>\n",
              "      <td>100.0</td>\n",
              "      <td>38.70</td>\n",
              "      <td>23.1855</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>13096 rows × 26 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
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              "    .colab-df-convert:hover {\n",
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              "    .colab-df-buttons div {\n",
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              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
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              "\n",
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              "      --hover-bg-color: #E2EBFA;\n",
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              "      --disabled-fill-color: #AAA;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
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              "      spin 1s steps(1) infinite;\n",
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              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
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              "    20% {\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "\n",
              "  <div id=\"id_7b927f44-846d-4637-a9da-fa3b961f7700\">\n",
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              "        border-radius: 50%;\n",
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              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
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              "\n",
              "      .colab-df-generate:hover {\n",
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              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "      [theme=dark] .colab-df-generate {\n",
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              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('test')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    <script>\n",
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('test');\n",
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              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "test"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def add_RUL_column(df):\n",
        "    max_time_cycles = df.groupby(by='unit_number')['time_cycles'].max()\n",
        "    merged = df.merge( max_time_cycles.to_frame(name='max_time_cycle'), left_on='unit_number',right_index=True)\n",
        "    merged[\"RUL\"] = merged[\"max_time_cycle\"] - merged['time_cycles']\n",
        "    merged = merged.drop(\"max_time_cycle\", axis=1)\n",
        "    return merged\n",
        "train = add_RUL_column(train)\n",
        "display(train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 444
        },
        "id": "ZU-wrEluXMuJ",
        "outputId": "67365a9c-e618-4d16-e20c-b76315ed5228"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "       unit_number  time_cycles  setting_1  setting_2  setting_3  sensor_1  \\\n",
              "0                1            1    -0.0007    -0.0004      100.0    518.67   \n",
              "1                1            2     0.0019    -0.0003      100.0    518.67   \n",
              "2                1            3    -0.0043     0.0003      100.0    518.67   \n",
              "3                1            4     0.0007     0.0000      100.0    518.67   \n",
              "4                1            5    -0.0019    -0.0002      100.0    518.67   \n",
              "...            ...          ...        ...        ...        ...       ...   \n",
              "20626          100          196    -0.0004    -0.0003      100.0    518.67   \n",
              "20627          100          197    -0.0016    -0.0005      100.0    518.67   \n",
              "20628          100          198     0.0004     0.0000      100.0    518.67   \n",
              "20629          100          199    -0.0011     0.0003      100.0    518.67   \n",
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              "\n",
              "       sensor_2  sensor_3  sensor_4  sensor_5  ...  sensor_13  sensor_14  \\\n",
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              "4        642.37   1582.85   1406.22     14.62  ...    2388.04    8133.80   \n",
              "...         ...       ...       ...       ...  ...        ...        ...   \n",
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              "20627    643.54   1604.50   1433.58     14.62  ...    2388.22    8136.50   \n",
              "20628    643.42   1602.46   1428.18     14.62  ...    2388.24    8141.05   \n",
              "20629    643.23   1605.26   1426.53     14.62  ...    2388.23    8139.29   \n",
              "20630    643.85   1600.38   1432.14     14.62  ...    2388.26    8137.33   \n",
              "\n",
              "       sensor_15  sensor_16  sensor_17  sensor_18  sensor_19  sensor_20  \\\n",
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              "1         8.4318       0.03        392       2388      100.0      39.00   \n",
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              "4         8.4294       0.03        393       2388      100.0      38.90   \n",
              "...          ...        ...        ...        ...        ...        ...   \n",
              "20626     8.4956       0.03        397       2388      100.0      38.49   \n",
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              "20630     8.5036       0.03        396       2388      100.0      38.37   \n",
              "\n",
              "       sensor_21  RUL  \n",
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              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-1cc39557-8135-41f6-a8e9-39e6a43c3974 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_b8bffdae-d8e1-450f-9705-9d62e0358b26\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('train')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_b8bffdae-d8e1-450f-9705-9d62e0358b26 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('train');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "train"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "maxrul_u = train.groupby('unit_number').max().reset_index()\n",
        "maxrul_u.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 256
        },
        "id": "yBHVTUlZXQCF",
        "outputId": "774a7413-4564-4c9d-ac40-0cced759270a"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   unit_number  time_cycles  setting_1  setting_2  setting_3  sensor_1  \\\n",
              "0            1          192     0.0047     0.0005      100.0    518.67   \n",
              "1            2          287     0.0076     0.0006      100.0    518.67   \n",
              "2            3          179     0.0058     0.0005      100.0    518.67   \n",
              "3            4          189     0.0059     0.0006      100.0    518.67   \n",
              "4            5          269     0.0055     0.0005      100.0    518.67   \n",
              "\n",
              "   sensor_2  sensor_3  sensor_4  sensor_5  ...  sensor_13  sensor_14  \\\n",
              "0    644.21   1605.44   1432.52     14.62  ...    2388.35    8140.58   \n",
              "1    643.94   1610.10   1431.17     14.62  ...    2388.26    8175.57   \n",
              "2    643.93   1606.50   1438.51     14.62  ...    2388.20    8255.34   \n",
              "3    644.53   1612.11   1434.12     14.62  ...    2388.17    8259.42   \n",
              "4    644.02   1609.41   1434.59     14.62  ...    2388.23    8215.19   \n",
              "\n",
              "   sensor_15  sensor_16  sensor_17  sensor_18  sensor_19  sensor_20  \\\n",
              "0     8.5227       0.03        398       2388      100.0      39.18   \n",
              "1     8.5377       0.03        398       2388      100.0      39.24   \n",
              "2     8.5363       0.03        399       2388      100.0      39.23   \n",
              "3     8.5462       0.03        399       2388      100.0      39.21   \n",
              "4     8.5410       0.03        398       2388      100.0      39.29   \n",
              "\n",
              "   sensor_21  RUL  \n",
              "0    23.4999  191  \n",
              "1    23.6005  286  \n",
              "2    23.5181  178  \n",
              "3    23.5074  188  \n",
              "4    23.5503  268  \n",
              "\n",
              "[5 rows x 27 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7f6cab77-a691-4bf6-855d-84dbcf5f93ce\" class=\"colab-df-container\">\n",
              "    <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>unit_number</th>\n",
              "      <th>time_cycles</th>\n",
              "      <th>setting_1</th>\n",
              "      <th>setting_2</th>\n",
              "      <th>setting_3</th>\n",
              "      <th>sensor_1</th>\n",
              "      <th>sensor_2</th>\n",
              "      <th>sensor_3</th>\n",
              "      <th>sensor_4</th>\n",
              "      <th>sensor_5</th>\n",
              "      <th>...</th>\n",
              "      <th>sensor_13</th>\n",
              "      <th>sensor_14</th>\n",
              "      <th>sensor_15</th>\n",
              "      <th>sensor_16</th>\n",
              "      <th>sensor_17</th>\n",
              "      <th>sensor_18</th>\n",
              "      <th>sensor_19</th>\n",
              "      <th>sensor_20</th>\n",
              "      <th>sensor_21</th>\n",
              "      <th>RUL</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>192</td>\n",
              "      <td>0.0047</td>\n",
              "      <td>0.0005</td>\n",
              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>644.21</td>\n",
              "      <td>1605.44</td>\n",
              "      <td>1432.52</td>\n",
              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>2388.35</td>\n",
              "      <td>8140.58</td>\n",
              "      <td>8.5227</td>\n",
              "      <td>0.03</td>\n",
              "      <td>398</td>\n",
              "      <td>2388</td>\n",
              "      <td>100.0</td>\n",
              "      <td>39.18</td>\n",
              "      <td>23.4999</td>\n",
              "      <td>191</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>287</td>\n",
              "      <td>0.0076</td>\n",
              "      <td>0.0006</td>\n",
              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>643.94</td>\n",
              "      <td>1610.10</td>\n",
              "      <td>1431.17</td>\n",
              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>2388.26</td>\n",
              "      <td>8175.57</td>\n",
              "      <td>8.5377</td>\n",
              "      <td>0.03</td>\n",
              "      <td>398</td>\n",
              "      <td>2388</td>\n",
              "      <td>100.0</td>\n",
              "      <td>39.24</td>\n",
              "      <td>23.6005</td>\n",
              "      <td>286</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>179</td>\n",
              "      <td>0.0058</td>\n",
              "      <td>0.0005</td>\n",
              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>643.93</td>\n",
              "      <td>1606.50</td>\n",
              "      <td>1438.51</td>\n",
              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>2388.20</td>\n",
              "      <td>8255.34</td>\n",
              "      <td>8.5363</td>\n",
              "      <td>0.03</td>\n",
              "      <td>399</td>\n",
              "      <td>2388</td>\n",
              "      <td>100.0</td>\n",
              "      <td>39.23</td>\n",
              "      <td>23.5181</td>\n",
              "      <td>178</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>189</td>\n",
              "      <td>0.0059</td>\n",
              "      <td>0.0006</td>\n",
              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>644.53</td>\n",
              "      <td>1612.11</td>\n",
              "      <td>1434.12</td>\n",
              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>2388.17</td>\n",
              "      <td>8259.42</td>\n",
              "      <td>8.5462</td>\n",
              "      <td>0.03</td>\n",
              "      <td>399</td>\n",
              "      <td>2388</td>\n",
              "      <td>100.0</td>\n",
              "      <td>39.21</td>\n",
              "      <td>23.5074</td>\n",
              "      <td>188</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>269</td>\n",
              "      <td>0.0055</td>\n",
              "      <td>0.0005</td>\n",
              "      <td>100.0</td>\n",
              "      <td>518.67</td>\n",
              "      <td>644.02</td>\n",
              "      <td>1609.41</td>\n",
              "      <td>1434.59</td>\n",
              "      <td>14.62</td>\n",
              "      <td>...</td>\n",
              "      <td>2388.23</td>\n",
              "      <td>8215.19</td>\n",
              "      <td>8.5410</td>\n",
              "      <td>0.03</td>\n",
              "      <td>398</td>\n",
              "      <td>2388</td>\n",
              "      <td>100.0</td>\n",
              "      <td>39.29</td>\n",
              "      <td>23.5503</td>\n",
              "      <td>268</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 27 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7f6cab77-a691-4bf6-855d-84dbcf5f93ce')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
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              "  <style>\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "\n",
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              "\n",
              "    .colab-df-buttons div {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
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              "        document.querySelector('#df-7f6cab77-a691-4bf6-855d-84dbcf5f93ce button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-7f6cab77-a691-4bf6-855d-84dbcf5f93ce');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
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              "      --hover-fill-color: #174EA6;\n",
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              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
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              "      --disabled-fill-color: #666;\n",
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              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
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              "    border-radius: 50%;\n",
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              "    display: none;\n",
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              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
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              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-7680ebb1-7ebd-4773-b77b-b5f091d9ec9d button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "maxrul_u"
            }
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "drop_labels1 = ['unit_number','time_cycles','setting_1','setting_2','setting_3','RUL']\n",
        "\n",
        "X = train.drop(drop_labels1,axis = 1)\n",
        "Y = train['RUL']\n",
        "\n",
        "X_train, X_valid, y_train, y_valid= train_test_split(X,Y, test_size=0.3, random_state=42)\n",
        "\n",
        "# Conserve only the last occurence of each unit to match the length of y_valid\n",
        "X_test = df_test.groupby('unit_number').last().reset_index().drop(columns=['unit_number','time_cycles','setting_1','setting_2','setting_3'])\n",
        "y_test = y_test.values.reshape(1,len(y_test))[0]"
      ],
      "metadata": {
        "id": "K9is4Da7XS88"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "28Fz7AA6XV8N",
        "outputId": "b65273f7-ebc2-42f2-c604-209ea832b56a"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['sensor_1', 'sensor_2', 'sensor_3', 'sensor_4', 'sensor_5', 'sensor_6',\n",
              "       'sensor_7', 'sensor_8', 'sensor_9', 'sensor_10', 'sensor_11',\n",
              "       'sensor_12', 'sensor_13', 'sensor_14', 'sensor_15', 'sensor_16',\n",
              "       'sensor_17', 'sensor_18', 'sensor_19', 'sensor_20', 'sensor_21'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "scaler = MinMaxScaler()\n",
        "X_train_s = pd.DataFrame( scaler.fit_transform(X_train), columns = X_train.columns )\n",
        "X_valid_s = pd.DataFrame( scaler.fit_transform(X_valid), columns = X_valid.columns )\n",
        "X_test_s = pd.DataFrame( scaler.fit_transform(X_test), columns = X_test.columns )"
      ],
      "metadata": {
        "id": "N1ti14cyXYPj"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def evaluate(y_true, y_hat, label='test'):\n",
        "  rmse = np.sqrt( mean_squared_error(y_true, y_hat) )\n",
        "  variance = r2_score(y_true, y_hat)\n",
        "  mae = mean_absolute_error(y_true, y_hat)\n",
        "  print('{} set RMSE:{}, R2:{}, MAE:{}'.format(label, rmse, variance,mae))\n",
        "\n",
        "#plot real data and the predicted one to make some comparison\n",
        "def plot_predActual(y_test, y_predictions,model_name):\n",
        "  plt.style.use('seaborn-white')\n",
        "  plt.rcParams['figure.figsize']=20,5\n",
        "  fig,ax = plt.subplots()\n",
        "  plt.title( model_name +' prediction result',fontsize =16)\n",
        "  plt.ylabel('RUL',fontsize =16)\n",
        "  plt.xlabel('Test Engine Units',fontsize =16)\n",
        "  g = sns.lineplot(x = np.arange(0,len(train['unit_number'].unique())),y = y_test,color='lightseagreen',label = 'actual',ax=ax)\n",
        "  f = sns.lineplot(x = np.arange(0,len(train['unit_number'].unique())),y = y_predictions,color='salmon',label = 'predictions',ax=ax)\n",
        "  ax.grid(True)\n",
        "  ax.legend()\n",
        "  plt.show()"
      ],
      "metadata": {
        "id": "Ac6viTH_XcCJ"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model_et = ExtraTreesRegressor(n_estimators = 500,n_jobs = -1,random_state=42)"
      ],
      "metadata": {
        "id": "jZq1VHAmXgE7"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "models = {\"DT\":model_et}"
      ],
      "metadata": {
        "id": "fkkidfd9XkG9"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for model_name, model in models.items():\n",
        "  print(\"================\",model_name,\"================\")\n",
        "  model.fit(X_train_s,y_train)\n",
        "  y_train_pred = model.predict(X_train_s) #Prediction on train data\n",
        "  evaluate(y_train, y_train_pred, label='train')\n",
        "\n",
        "  y_valid_pred = model.predict(X_valid_s) #Prediction on validation data\n",
        "  evaluate(y_valid, y_valid_pred, label='valid')\n",
        "\n",
        "  y_test_pred = model.predict(X_test_s)  #Prediction on test data\n",
        "  evaluate(y_test, y_test_pred, label='test')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0IQ3nOjNXp9h",
        "outputId": "c77a6be2-ddbd-4e92-badb-ed032aa38266"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "================ DT ================\n",
            "train set RMSE:0.0, R2:1.0, MAE:0.0\n",
            "valid set RMSE:44.683308544851265, R2:0.56409722729205, MAE:31.308119224555735\n",
            "test set RMSE:31.56638499163311, R2:0.42298094688794086, MAE:24.836440000000003\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "THCUguzuXcFD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "isF2t1FEV9sh"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "7wr5hreQV4pJ"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}