stock_prediction.ipynb

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      "name": "python3",
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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Rudraps07/Nifty-fifty-stock-market-prediction-model/blob/main/DT_project.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
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        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rXxMjJ3SlBqT",
        "outputId": "8e34047c-641b-4fcb-f95b-3452d61a0a4c"
      },
      "source": [
        "import numpy as np \n",
        "import pandas as pd \n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "print(\"import complete\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "import complete\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_excel('data (2).xlsx')\n",
        "df.head()"
      ],
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          "height": 206
        },
        "id": "dla9mb9XKFf6",
        "outputId": "a77379f9-a23c-4403-ac96-aacc0e5df697"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        Date      Open      High       Low     Close  Shares Traded  Turnover\n",
              "0 2021-08-31  16947.50  17153.50  16915.85  17132.20      464390247  40147.89\n",
              "1 2021-09-01  17185.60  17225.75  17055.05  17076.25      301894634  27691.93\n",
              "2 2021-09-02  17095.40  17245.50  17059.70  17234.15      242377518  22620.36\n",
              "3 2021-09-03  17262.45  17340.10  17212.20  17323.60      261373795  23579.17\n",
              "4 2021-09-06  17399.35  17429.55  17345.55  17377.80      228045532  21270.62"
            ],
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Shares Traded</th>\n",
              "      <th>Turnover</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2021-08-31</td>\n",
              "      <td>16947.50</td>\n",
              "      <td>17153.50</td>\n",
              "      <td>16915.85</td>\n",
              "      <td>17132.20</td>\n",
              "      <td>464390247</td>\n",
              "      <td>40147.89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2021-09-01</td>\n",
              "      <td>17185.60</td>\n",
              "      <td>17225.75</td>\n",
              "      <td>17055.05</td>\n",
              "      <td>17076.25</td>\n",
              "      <td>301894634</td>\n",
              "      <td>27691.93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2021-09-02</td>\n",
              "      <td>17095.40</td>\n",
              "      <td>17245.50</td>\n",
              "      <td>17059.70</td>\n",
              "      <td>17234.15</td>\n",
              "      <td>242377518</td>\n",
              "      <td>22620.36</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2021-09-03</td>\n",
              "      <td>17262.45</td>\n",
              "      <td>17340.10</td>\n",
              "      <td>17212.20</td>\n",
              "      <td>17323.60</td>\n",
              "      <td>261373795</td>\n",
              "      <td>23579.17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2021-09-06</td>\n",
              "      <td>17399.35</td>\n",
              "      <td>17429.55</td>\n",
              "      <td>17345.55</td>\n",
              "      <td>17377.80</td>\n",
              "      <td>228045532</td>\n",
              "      <td>21270.62</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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          "metadata": {},
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    {
      "cell_type": "code",
      "source": [
        "fig, ax = plt.subplots(figsize=(10,10))  \n",
        "dataplot = sns.heatmap(df.corr(), cmap=\"YlGnBu\", annot=True)"
      ],
      "metadata": {
        "colab": {
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          "height": 596
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        "outputId": "52e797ca-0ab0-4ea3-ae73-0f0e1ee0d841"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 2 Axes>"
            ],
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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data = df[['Date','Open','High','Low','Shares Traded','Turnover']]"
      ],
      "metadata": {
        "id": "wyo6pZa8N_TP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.set_index(\"Date\", drop=False, inplace=True)"
      ],
      "metadata": {
        "id": "eaYpkxrXOIcf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.Close.plot(figsize=(14, 7))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "id": "xHyBbJYCONpn",
        "outputId": "f3c0de01-c04f-46c6-b607-12ed63e8c4a2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9c50a21e90>"
            ]
          },
          "metadata": {},
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1008x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.info()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LIBnf1qNOlJV",
        "outputId": "2f56ef2d-7288-43e0-e130-c1b438ff18d0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 247 entries, 0 to 246\n",
            "Data columns (total 6 columns):\n",
            " #   Column         Non-Null Count  Dtype         \n",
            "---  ------         --------------  -----         \n",
            " 0   Date           247 non-null    datetime64[ns]\n",
            " 1   Open           247 non-null    float64       \n",
            " 2   High           247 non-null    float64       \n",
            " 3   Low            247 non-null    float64       \n",
            " 4   Shares Traded  247 non-null    int64         \n",
            " 5   Turnover       247 non-null    float64       \n",
            "dtypes: datetime64[ns](1), float64(4), int64(1)\n",
            "memory usage: 11.7 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.reset_index(drop=True, inplace=True)\n",
        "lag_features = [\"Open\",\"High\", \"Low\"]\n",
        "window1 = 4\n",
        "window2 = 7\n",
        "\n",
        "df_rolled_3d = df[lag_features].rolling(window=window1, min_periods=0)\n",
        "df_mean_3d = df_rolled_3d.mean().shift(1).reset_index().astype(np.float32)\n",
        "\n",
        "df_rolled_7d = df[lag_features].rolling(window=window2, min_periods=0)\n",
        "df_std_7d = df_rolled_7d.std().shift(1).reset_index().astype(np.float32)\n",
        "\n",
        "for feature in lag_features:\n",
        "    df[f\"{feature}_mean_lag{window1}\"] = df_mean_3d[feature].astype('float32')\n",
        "    df[f\"{feature}_std_lag{window2}\"] = df_std_7d[feature].astype('float32')"
      ],
      "metadata": {
        "id": "pmlgILsjOuW5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.fillna(df.mean(), inplace=True)"
      ],
      "metadata": {
        "id": "wDzHe01cO63x",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "290be07f-5609-41f5-8a1c-68f21409f162"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: FutureWarning: DataFrame.mean and DataFrame.median with numeric_only=None will include datetime64 and datetime64tz columns in a future version.\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.set_index(\"Date\", drop=False, inplace=True)\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        },
        "id": "MWU0cT6YPP-U",
        "outputId": "6e01b88b-538d-49e9-c980-df00514325bc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                 Date      Open      High       Low     Close  Shares Traded  \\\n",
              "Date                                                                           \n",
              "2021-08-31 2021-08-31  16947.50  17153.50  16915.85  17132.20      464390247   \n",
              "2021-09-01 2021-09-01  17185.60  17225.75  17055.05  17076.25      301894634   \n",
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              "2021-09-03 2021-09-03  17262.45  17340.10  17212.20  17323.60      261373795   \n",
              "2021-09-06 2021-09-06  17399.35  17429.55  17345.55  17377.80      228045532   \n",
              "\n",
              "            Turnover  Open_mean_lag4  Open_std_lag7  High_mean_lag4  \\\n",
              "Date                                                                  \n",
              "2021-08-31  40147.89    17133.507812     203.013016    17226.335938   \n",
              "2021-09-01  27691.93    16947.500000     203.013016    17153.500000   \n",
              "2021-09-02  22620.36    17066.550781     168.362122    17189.625000   \n",
              "2021-09-03  23579.17    17076.166016     120.209579    17208.250000   \n",
              "2021-09-06  21270.62    17122.738281     135.310501    17241.212891   \n",
              "\n",
              "            High_std_lag7  Low_mean_lag4  Low_std_lag7  \n",
              "Date                                                    \n",
              "2021-08-31     183.286224   17010.503906    207.852936  \n",
              "2021-09-01     183.286224   16915.849609    207.852936  \n",
              "2021-09-02      51.088467   16985.449219     98.429260  \n",
              "2021-09-03      48.432297   17010.199219     81.742569  \n",
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          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Date = pd.to_datetime(df.Date, format=\"%d-%m-%Y\")\n",
        "df[\"month\"] = df.Date.dt.month\n",
        "df[\"day\"] = df.Date.dt.day\n",
        "df[\"day_of_week\"] = df.Date.dt.dayofweek\n",
        "df.head()"
      ],
      "metadata": {
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          "height": 406
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        "id": "0DcILsZoPSha",
        "outputId": "6bbb25a4-f58b-44a1-c4d1-294402acbd4e"
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      "execution_count": null,
      "outputs": [
        {
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              "                 Date      Open      High       Low     Close  Shares Traded  \\\n",
              "Date                                                                           \n",
              "2021-08-31 2021-08-31  16947.50  17153.50  16915.85  17132.20      464390247   \n",
              "2021-09-01 2021-09-01  17185.60  17225.75  17055.05  17076.25      301894634   \n",
              "2021-09-02 2021-09-02  17095.40  17245.50  17059.70  17234.15      242377518   \n",
              "2021-09-03 2021-09-03  17262.45  17340.10  17212.20  17323.60      261373795   \n",
              "2021-09-06 2021-09-06  17399.35  17429.55  17345.55  17377.80      228045532   \n",
              "\n",
              "            Turnover  Open_mean_lag4  Open_std_lag7  High_mean_lag4  \\\n",
              "Date                                                                  \n",
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              "\n",
              "            High_std_lag7  Low_mean_lag4  Low_std_lag7  month  day  \\\n",
              "Date                                                                 \n",
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              "2021-09-01     183.286224   16915.849609    207.852936      9    1   \n",
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              "\n",
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              "\n",
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              "\n",
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              "        buttonEl.style.display =\n",
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              "            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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_train = df[df.Date >= \"2022\"]\n",
        "df_valid = df[df.Date >= \"2022\"]\n"
      ],
      "metadata": {
        "id": "JUbtSERdPZP7"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_valid.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hd-iJPnHPbPr",
        "outputId": "94ee272e-4d48-4e11-c813-ea82b970190f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(162, 16)"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install keras\n",
        "import tensorflow\n",
        "from sklearn.preprocessing import MinMaxScaler"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i1zLZQraQaBY",
        "outputId": "e53a291d-fb1f-456c-b615-8a66f5ac5a71"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: keras in /usr/local/lib/python3.7/dist-packages (2.8.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_train.head().T"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 551
        },
        "id": "9cksHTY4Qeci",
        "outputId": "495382af-d165-4c0a-8fc6-0ceaea532a11"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Date                     2022-01-03           2022-01-04           2022-01-05  \\\n",
              "Date            2022-01-03 00:00:00  2022-01-04 00:00:00  2022-01-05 00:00:00   \n",
              "Open                       17387.15              17681.4              17820.1   \n",
              "High                       17646.65              17827.6              17944.7   \n",
              "Low                         17383.3             17593.55             17748.85   \n",
              "Close                       17625.7             17805.25             17925.25   \n",
              "Shares Traded             200456430            247437472            251460038   \n",
              "Turnover                   16181.36             18604.16             23737.31   \n",
              "Open_mean_lag4         17210.912109         17263.300781            17378.625   \n",
              "Open_std_lag7            107.109695           134.337357             227.1241   \n",
              "High_mean_lag4         17300.261719         17399.363281         17534.775391   \n",
              "High_std_lag7            104.598923           178.154724           251.821976   \n",
              "Low_mean_lag4          17180.662109         17236.199219         17340.425781   \n",
              "Low_std_lag7             152.019592           189.507019           233.424591   \n",
              "month                             1                    1                    1   \n",
              "day                               3                    4                    5   \n",
              "day_of_week                       0                    1                    2   \n",
              "\n",
              "Date                     2022-01-06           2022-01-07  \n",
              "Date            2022-01-06 00:00:00  2022-01-07 00:00:00  \n",
              "Open                        17768.5              17797.6  \n",
              "High                       17797.95              17905.0  \n",
              "Low                        17655.55             17704.55  \n",
              "Close                       17745.9              17812.7  \n",
              "Shares Traded             236454824            239338015  \n",
              "Turnover                   22643.82             21447.89  \n",
              "Open_mean_lag4         17533.287109         17664.287109  \n",
              "Open_std_lag7            258.395203           273.400879  \n",
              "High_mean_lag4           17704.9375         17804.224609  \n",
              "High_std_lag7            288.165009           277.789398  \n",
              "Low_mean_lag4          17491.050781           17595.3125  \n",
              "Low_std_lag7             237.741653           245.675034  \n",
              "month                             1                    1  \n",
              "day                               6                    7  \n",
              "day_of_week                       3                    4  "
            ],
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              "      <th>2022-01-03</th>\n",
              "      <th>2022-01-04</th>\n",
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              "      <th>Date</th>\n",
              "      <td>2022-01-03 00:00:00</td>\n",
              "      <td>2022-01-04 00:00:00</td>\n",
              "      <td>2022-01-05 00:00:00</td>\n",
              "      <td>2022-01-06 00:00:00</td>\n",
              "      <td>2022-01-07 00:00:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Open</th>\n",
              "      <td>17387.15</td>\n",
              "      <td>17681.4</td>\n",
              "      <td>17820.1</td>\n",
              "      <td>17768.5</td>\n",
              "      <td>17797.6</td>\n",
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              "      <th>High</th>\n",
              "      <td>17646.65</td>\n",
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              "      <td>17383.3</td>\n",
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              "      <td>17655.55</td>\n",
              "      <td>17704.55</td>\n",
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              "      <th>Close</th>\n",
              "      <td>17625.7</td>\n",
              "      <td>17805.25</td>\n",
              "      <td>17925.25</td>\n",
              "      <td>17745.9</td>\n",
              "      <td>17812.7</td>\n",
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              "      <td>200456430</td>\n",
              "      <td>247437472</td>\n",
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              "      <td>236454824</td>\n",
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              "      <th>Turnover</th>\n",
              "      <td>16181.36</td>\n",
              "      <td>18604.16</td>\n",
              "      <td>23737.31</td>\n",
              "      <td>22643.82</td>\n",
              "      <td>21447.89</td>\n",
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              "    <tr>\n",
              "      <th>Open_mean_lag4</th>\n",
              "      <td>17210.912109</td>\n",
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              "      <th>Open_std_lag7</th>\n",
              "      <td>107.109695</td>\n",
              "      <td>134.337357</td>\n",
              "      <td>227.1241</td>\n",
              "      <td>258.395203</td>\n",
              "      <td>273.400879</td>\n",
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              "    <tr>\n",
              "      <th>High_mean_lag4</th>\n",
              "      <td>17300.261719</td>\n",
              "      <td>17399.363281</td>\n",
              "      <td>17534.775391</td>\n",
              "      <td>17704.9375</td>\n",
              "      <td>17804.224609</td>\n",
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              "      <th>High_std_lag7</th>\n",
              "      <td>104.598923</td>\n",
              "      <td>178.154724</td>\n",
              "      <td>251.821976</td>\n",
              "      <td>288.165009</td>\n",
              "      <td>277.789398</td>\n",
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              "      <th>Low_mean_lag4</th>\n",
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              "      <td>17236.199219</td>\n",
              "      <td>17340.425781</td>\n",
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              "      <td>17595.3125</td>\n",
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              "      <th>Low_std_lag7</th>\n",
              "      <td>152.019592</td>\n",
              "      <td>189.507019</td>\n",
              "      <td>233.424591</td>\n",
              "      <td>237.741653</td>\n",
              "      <td>245.675034</td>\n",
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              "    <tr>\n",
              "      <th>month</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>day</th>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>day_of_week</th>\n",
              "      <td>0</td>\n",
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              "          const element = document.querySelector('#df-b8611e0f-8b3e-437f-ba16-9454c8128f27');\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_train = df_train[\"Close\"]\n",
        "scaler=MinMaxScaler(feature_range=(0,1))\n",
        "y_train1=scaler.fit_transform(np.array(df_train['Close']).reshape(-1,1))\n",
        "y_trainn = df_train[\"Close\"].to_numpy().reshape(-1,1)"
      ],
      "metadata": {
        "id": "U-ln1fZ9Qie8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y_valid = df_valid[\"Close\"]\n",
        "scaler1=MinMaxScaler(feature_range=(0,1))\n",
        "y_valid1=scaler1.fit_transform(np.array(df_valid['Close']).reshape(-1,1))\n",
        "y_validn = df_valid[\"Close\"].to_numpy().reshape(-1,1)"
      ],
      "metadata": {
        "id": "5MpawXD9Qk2L"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train = df_train.drop(columns=[\"Close\"])\n",
        "X_train1 = X_train.drop(\"Date\", axis=1)\n",
        "X_train1 = (X_train1-X_train1.min())/(X_train1.max()-X_train1.min())\n",
        "X_train2 = pd.concat((X_train1, X_train.Date), 1)"
      ],
      "metadata": {
        "id": "318XELeEQm7v",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "722b482a-c3e9-47e0-efd7-68740536c562"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: FutureWarning: In a future version of pandas all arguments of concat except for the argument 'objs' will be keyword-only\n",
            "  after removing the cwd from sys.path.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_valid = df_valid.drop(columns=[\"Close\"])\n",
        "X_valid1 = X_valid.drop(\"Date\", axis=1)\n",
        "X_valid1 = (X_valid1-X_valid1.min())/(X_valid1.max()-X_valid1.min())\n",
        "X_valid2 = pd.concat((X_valid1, X_valid.Date), 1)"
      ],
      "metadata": {
        "id": "mNiwdhCxQ4w_",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f68afa67-b12d-405a-85d9-02823dc8a4dd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: FutureWarning: In a future version of pandas all arguments of concat except for the argument 'objs' will be keyword-only\n",
            "  after removing the cwd from sys.path.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_train3 = X_train2.drop(columns=['Date']).to_numpy()\n",
        "X_valid3 = X_valid2.drop(columns=['Date']).to_numpy()"
      ],
      "metadata": {
        "id": "k3UHJqzIREbM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y_train1 = y_train1.reshape(-1,1)\n",
        "y_valid1 = y_valid1.reshape(-1,1)"
      ],
      "metadata": {
        "id": "xZSSIJ4sRHC5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install xgboost\n",
        "import xgboost as xgb\n",
        "import sklearn\n",
        "from xgboost import XGBRegressor\n",
        "from xgboost import plot_importance"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hvWrMptMRKqC",
        "outputId": "cccd5984-837e-43fa-8c33-bb183ed4b0f2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: xgboost in /usr/local/lib/python3.7/dist-packages (0.90)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.7/dist-packages (from xgboost) (1.7.3)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from xgboost) (1.21.6)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "xgb = XGBRegressor(n_estimators=1000,learning_rate=0.01)\n",
        "xgb\n",
        "\n",
        "xgb.fit(X_train3,y_train1,eval_set=[(X_train3,y_train1),(X_valid3,y_valid1)],early_stopping_rounds=100,verbose=True) # Change verbose to True if you want to see it train"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "voCFYySBRPsX",
        "outputId": "4cee3678-f3b2-4961-cce6-476e9be50281"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[16:07:35] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
            "[0]\tvalidation_0-rmse:0.246255\tvalidation_1-rmse:0.246255\n",
            "Multiple eval metrics have been passed: 'validation_1-rmse' will be used for early stopping.\n",
            "\n",
            "Will train until validation_1-rmse hasn't improved in 100 rounds.\n",
            "[1]\tvalidation_0-rmse:0.243975\tvalidation_1-rmse:0.243975\n",
            "[2]\tvalidation_0-rmse:0.241718\tvalidation_1-rmse:0.241718\n",
            "[3]\tvalidation_0-rmse:0.239483\tvalidation_1-rmse:0.239483\n",
            "[4]\tvalidation_0-rmse:0.23727\tvalidation_1-rmse:0.23727\n",
            "[5]\tvalidation_0-rmse:0.235079\tvalidation_1-rmse:0.235079\n",
            "[6]\tvalidation_0-rmse:0.232903\tvalidation_1-rmse:0.232903\n",
            "[7]\tvalidation_0-rmse:0.230755\tvalidation_1-rmse:0.230755\n",
            "[8]\tvalidation_0-rmse:0.228621\tvalidation_1-rmse:0.228621\n",
            "[9]\tvalidation_0-rmse:0.226514\tvalidation_1-rmse:0.226514\n",
            "[10]\tvalidation_0-rmse:0.224422\tvalidation_1-rmse:0.224422\n",
            "[11]\tvalidation_0-rmse:0.222357\tvalidation_1-rmse:0.222357\n",
            "[12]\tvalidation_0-rmse:0.220305\tvalidation_1-rmse:0.220305\n",
            "[13]\tvalidation_0-rmse:0.218279\tvalidation_1-rmse:0.218279\n",
            "[14]\tvalidation_0-rmse:0.216267\tvalidation_1-rmse:0.216267\n",
            "[15]\tvalidation_0-rmse:0.214279\tvalidation_1-rmse:0.214279\n",
            "[16]\tvalidation_0-rmse:0.212306\tvalidation_1-rmse:0.212306\n",
            "[17]\tvalidation_0-rmse:0.210357\tvalidation_1-rmse:0.210357\n",
            "[18]\tvalidation_0-rmse:0.208422\tvalidation_1-rmse:0.208422\n",
            "[19]\tvalidation_0-rmse:0.206511\tvalidation_1-rmse:0.206511\n",
            "[20]\tvalidation_0-rmse:0.204613\tvalidation_1-rmse:0.204613\n",
            "[21]\tvalidation_0-rmse:0.202738\tvalidation_1-rmse:0.202738\n",
            "[22]\tvalidation_0-rmse:0.200879\tvalidation_1-rmse:0.200879\n",
            "[23]\tvalidation_0-rmse:0.19904\tvalidation_1-rmse:0.19904\n",
            "[24]\tvalidation_0-rmse:0.197215\tvalidation_1-rmse:0.197215\n",
            "[25]\tvalidation_0-rmse:0.195413\tvalidation_1-rmse:0.195413\n",
            "[26]\tvalidation_0-rmse:0.193626\tvalidation_1-rmse:0.193626\n",
            "[27]\tvalidation_0-rmse:0.191856\tvalidation_1-rmse:0.191856\n",
            "[28]\tvalidation_0-rmse:0.190102\tvalidation_1-rmse:0.190102\n",
            "[29]\tvalidation_0-rmse:0.188365\tvalidation_1-rmse:0.188365\n",
            "[30]\tvalidation_0-rmse:0.186646\tvalidation_1-rmse:0.186646\n",
            "[31]\tvalidation_0-rmse:0.184942\tvalidation_1-rmse:0.184942\n",
            "[32]\tvalidation_0-rmse:0.183256\tvalidation_1-rmse:0.183256\n",
            "[33]\tvalidation_0-rmse:0.181586\tvalidation_1-rmse:0.181586\n",
            "[34]\tvalidation_0-rmse:0.179932\tvalidation_1-rmse:0.179932\n",
            "[35]\tvalidation_0-rmse:0.178295\tvalidation_1-rmse:0.178295\n",
            "[36]\tvalidation_0-rmse:0.176673\tvalidation_1-rmse:0.176673\n",
            "[37]\tvalidation_0-rmse:0.175064\tvalidation_1-rmse:0.175064\n",
            "[38]\tvalidation_0-rmse:0.173475\tvalidation_1-rmse:0.173475\n",
            "[39]\tvalidation_0-rmse:0.1719\tvalidation_1-rmse:0.1719\n",
            "[40]\tvalidation_0-rmse:0.170337\tvalidation_1-rmse:0.170337\n",
            "[41]\tvalidation_0-rmse:0.168792\tvalidation_1-rmse:0.168792\n",
            "[42]\tvalidation_0-rmse:0.167261\tvalidation_1-rmse:0.167261\n",
            "[43]\tvalidation_0-rmse:0.165746\tvalidation_1-rmse:0.165746\n",
            "[44]\tvalidation_0-rmse:0.164238\tvalidation_1-rmse:0.164238\n",
            "[45]\tvalidation_0-rmse:0.162752\tvalidation_1-rmse:0.162752\n",
            "[46]\tvalidation_0-rmse:0.161275\tvalidation_1-rmse:0.161275\n",
            "[47]\tvalidation_0-rmse:0.159816\tvalidation_1-rmse:0.159816\n",
            "[48]\tvalidation_0-rmse:0.158366\tvalidation_1-rmse:0.158366\n",
            "[49]\tvalidation_0-rmse:0.156936\tvalidation_1-rmse:0.156936\n",
            "[50]\tvalidation_0-rmse:0.155514\tvalidation_1-rmse:0.155514\n",
            "[51]\tvalidation_0-rmse:0.154108\tvalidation_1-rmse:0.154108\n",
            "[52]\tvalidation_0-rmse:0.152715\tvalidation_1-rmse:0.152715\n",
            "[53]\tvalidation_0-rmse:0.151337\tvalidation_1-rmse:0.151337\n",
            "[54]\tvalidation_0-rmse:0.149966\tvalidation_1-rmse:0.149966\n",
            "[55]\tvalidation_0-rmse:0.148614\tvalidation_1-rmse:0.148614\n",
            "[56]\tvalidation_0-rmse:0.14727\tvalidation_1-rmse:0.14727\n",
            "[57]\tvalidation_0-rmse:0.145938\tvalidation_1-rmse:0.145938\n",
            "[58]\tvalidation_0-rmse:0.144625\tvalidation_1-rmse:0.144625\n",
            "[59]\tvalidation_0-rmse:0.143319\tvalidation_1-rmse:0.143319\n",
            "[60]\tvalidation_0-rmse:0.142026\tvalidation_1-rmse:0.142026\n",
            "[61]\tvalidation_0-rmse:0.140749\tvalidation_1-rmse:0.140749\n",
            "[62]\tvalidation_0-rmse:0.139478\tvalidation_1-rmse:0.139478\n",
            "[63]\tvalidation_0-rmse:0.138222\tvalidation_1-rmse:0.138222\n",
            "[64]\tvalidation_0-rmse:0.136976\tvalidation_1-rmse:0.136976\n",
            "[65]\tvalidation_0-rmse:0.135742\tvalidation_1-rmse:0.135742\n",
            "[66]\tvalidation_0-rmse:0.134522\tvalidation_1-rmse:0.134522\n",
            "[67]\tvalidation_0-rmse:0.133316\tvalidation_1-rmse:0.133316\n",
            "[68]\tvalidation_0-rmse:0.132123\tvalidation_1-rmse:0.132123\n",
            "[69]\tvalidation_0-rmse:0.130937\tvalidation_1-rmse:0.130937\n",
            "[70]\tvalidation_0-rmse:0.129761\tvalidation_1-rmse:0.129761\n",
            "[71]\tvalidation_0-rmse:0.128596\tvalidation_1-rmse:0.128596\n",
            "[72]\tvalidation_0-rmse:0.127447\tvalidation_1-rmse:0.127447\n",
            "[73]\tvalidation_0-rmse:0.126309\tvalidation_1-rmse:0.126309\n",
            "[74]\tvalidation_0-rmse:0.125178\tvalidation_1-rmse:0.125178\n",
            "[75]\tvalidation_0-rmse:0.124058\tvalidation_1-rmse:0.124058\n",
            "[76]\tvalidation_0-rmse:0.122952\tvalidation_1-rmse:0.122952\n",
            "[77]\tvalidation_0-rmse:0.121855\tvalidation_1-rmse:0.121855\n",
            "[78]\tvalidation_0-rmse:0.12077\tvalidation_1-rmse:0.12077\n",
            "[79]\tvalidation_0-rmse:0.119696\tvalidation_1-rmse:0.119696\n",
            "[80]\tvalidation_0-rmse:0.118631\tvalidation_1-rmse:0.118631\n",
            "[81]\tvalidation_0-rmse:0.117578\tvalidation_1-rmse:0.117578\n",
            "[82]\tvalidation_0-rmse:0.116535\tvalidation_1-rmse:0.116535\n",
            "[83]\tvalidation_0-rmse:0.115497\tvalidation_1-rmse:0.115497\n",
            "[84]\tvalidation_0-rmse:0.114473\tvalidation_1-rmse:0.114473\n",
            "[85]\tvalidation_0-rmse:0.113457\tvalidation_1-rmse:0.113457\n",
            "[86]\tvalidation_0-rmse:0.112454\tvalidation_1-rmse:0.112454\n",
            "[87]\tvalidation_0-rmse:0.111455\tvalidation_1-rmse:0.111455\n",
            "[88]\tvalidation_0-rmse:0.11047\tvalidation_1-rmse:0.11047\n",
            "[89]\tvalidation_0-rmse:0.109492\tvalidation_1-rmse:0.109492\n",
            "[90]\tvalidation_0-rmse:0.108527\tvalidation_1-rmse:0.108527\n",
            "[91]\tvalidation_0-rmse:0.107569\tvalidation_1-rmse:0.107569\n",
            "[92]\tvalidation_0-rmse:0.106621\tvalidation_1-rmse:0.106621\n",
            "[93]\tvalidation_0-rmse:0.105682\tvalidation_1-rmse:0.105682\n",
            "[94]\tvalidation_0-rmse:0.10475\tvalidation_1-rmse:0.10475\n",
            "[95]\tvalidation_0-rmse:0.103829\tvalidation_1-rmse:0.103829\n",
            "[96]\tvalidation_0-rmse:0.102917\tvalidation_1-rmse:0.102917\n",
            "[97]\tvalidation_0-rmse:0.102014\tvalidation_1-rmse:0.102014\n",
            "[98]\tvalidation_0-rmse:0.101118\tvalidation_1-rmse:0.101118\n",
            "[99]\tvalidation_0-rmse:0.100231\tvalidation_1-rmse:0.100231\n",
            "[100]\tvalidation_0-rmse:0.09935\tvalidation_1-rmse:0.09935\n",
            "[101]\tvalidation_0-rmse:0.09848\tvalidation_1-rmse:0.09848\n",
            "[102]\tvalidation_0-rmse:0.097619\tvalidation_1-rmse:0.097619\n",
            "[103]\tvalidation_0-rmse:0.096765\tvalidation_1-rmse:0.096765\n",
            "[104]\tvalidation_0-rmse:0.095917\tvalidation_1-rmse:0.095917\n",
            "[105]\tvalidation_0-rmse:0.09508\tvalidation_1-rmse:0.09508\n",
            "[106]\tvalidation_0-rmse:0.094252\tvalidation_1-rmse:0.094252\n",
            "[107]\tvalidation_0-rmse:0.09343\tvalidation_1-rmse:0.09343\n",
            "[108]\tvalidation_0-rmse:0.092616\tvalidation_1-rmse:0.092616\n",
            "[109]\tvalidation_0-rmse:0.091811\tvalidation_1-rmse:0.091811\n",
            "[110]\tvalidation_0-rmse:0.091013\tvalidation_1-rmse:0.091013\n",
            "[111]\tvalidation_0-rmse:0.090224\tvalidation_1-rmse:0.090224\n",
            "[112]\tvalidation_0-rmse:0.08944\tvalidation_1-rmse:0.08944\n",
            "[113]\tvalidation_0-rmse:0.088663\tvalidation_1-rmse:0.088663\n",
            "[114]\tvalidation_0-rmse:0.087896\tvalidation_1-rmse:0.087896\n",
            "[115]\tvalidation_0-rmse:0.087134\tvalidation_1-rmse:0.087134\n",
            "[116]\tvalidation_0-rmse:0.086381\tvalidation_1-rmse:0.086381\n",
            "[117]\tvalidation_0-rmse:0.085634\tvalidation_1-rmse:0.085634\n",
            "[118]\tvalidation_0-rmse:0.084893\tvalidation_1-rmse:0.084893\n",
            "[119]\tvalidation_0-rmse:0.084162\tvalidation_1-rmse:0.084162\n",
            "[120]\tvalidation_0-rmse:0.083437\tvalidation_1-rmse:0.083437\n",
            "[121]\tvalidation_0-rmse:0.082718\tvalidation_1-rmse:0.082718\n",
            "[122]\tvalidation_0-rmse:0.082006\tvalidation_1-rmse:0.082006\n",
            "[123]\tvalidation_0-rmse:0.081302\tvalidation_1-rmse:0.081302\n",
            "[124]\tvalidation_0-rmse:0.080605\tvalidation_1-rmse:0.080605\n",
            "[125]\tvalidation_0-rmse:0.079914\tvalidation_1-rmse:0.079914\n",
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            "[127]\tvalidation_0-rmse:0.078551\tvalidation_1-rmse:0.078551\n",
            "[128]\tvalidation_0-rmse:0.077878\tvalidation_1-rmse:0.077878\n",
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            "[133]\tvalidation_0-rmse:0.074617\tvalidation_1-rmse:0.074617\n",
            "[134]\tvalidation_0-rmse:0.073983\tvalidation_1-rmse:0.073983\n",
            "[135]\tvalidation_0-rmse:0.073357\tvalidation_1-rmse:0.073357\n",
            "[136]\tvalidation_0-rmse:0.072735\tvalidation_1-rmse:0.072735\n",
            "[137]\tvalidation_0-rmse:0.072119\tvalidation_1-rmse:0.072119\n",
            "[138]\tvalidation_0-rmse:0.071511\tvalidation_1-rmse:0.071511\n",
            "[139]\tvalidation_0-rmse:0.070907\tvalidation_1-rmse:0.070907\n",
            "[140]\tvalidation_0-rmse:0.07031\tvalidation_1-rmse:0.07031\n",
            "[141]\tvalidation_0-rmse:0.069718\tvalidation_1-rmse:0.069718\n",
            "[142]\tvalidation_0-rmse:0.069132\tvalidation_1-rmse:0.069132\n",
            "[143]\tvalidation_0-rmse:0.068551\tvalidation_1-rmse:0.068551\n",
            "[144]\tvalidation_0-rmse:0.067978\tvalidation_1-rmse:0.067978\n",
            "[145]\tvalidation_0-rmse:0.067408\tvalidation_1-rmse:0.067408\n",
            "[146]\tvalidation_0-rmse:0.066845\tvalidation_1-rmse:0.066845\n",
            "[147]\tvalidation_0-rmse:0.066287\tvalidation_1-rmse:0.066287\n",
            "[148]\tvalidation_0-rmse:0.065735\tvalidation_1-rmse:0.065735\n",
            "[149]\tvalidation_0-rmse:0.065187\tvalidation_1-rmse:0.065187\n",
            "[150]\tvalidation_0-rmse:0.064645\tvalidation_1-rmse:0.064645\n",
            "[151]\tvalidation_0-rmse:0.064108\tvalidation_1-rmse:0.064108\n",
            "[152]\tvalidation_0-rmse:0.063578\tvalidation_1-rmse:0.063578\n",
            "[153]\tvalidation_0-rmse:0.063051\tvalidation_1-rmse:0.063051\n",
            "[154]\tvalidation_0-rmse:0.062531\tvalidation_1-rmse:0.062531\n",
            "[155]\tvalidation_0-rmse:0.062015\tvalidation_1-rmse:0.062015\n",
            "[156]\tvalidation_0-rmse:0.061504\tvalidation_1-rmse:0.061504\n",
            "[157]\tvalidation_0-rmse:0.060997\tvalidation_1-rmse:0.060997\n",
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            "[159]\tvalidation_0-rmse:0.060001\tvalidation_1-rmse:0.060001\n",
            "[160]\tvalidation_0-rmse:0.059509\tvalidation_1-rmse:0.059509\n",
            "[161]\tvalidation_0-rmse:0.059023\tvalidation_1-rmse:0.059023\n",
            "[162]\tvalidation_0-rmse:0.058541\tvalidation_1-rmse:0.058541\n",
            "[163]\tvalidation_0-rmse:0.058065\tvalidation_1-rmse:0.058065\n",
            "[164]\tvalidation_0-rmse:0.057593\tvalidation_1-rmse:0.057593\n",
            "[165]\tvalidation_0-rmse:0.057125\tvalidation_1-rmse:0.057125\n",
            "[166]\tvalidation_0-rmse:0.056662\tvalidation_1-rmse:0.056662\n",
            "[167]\tvalidation_0-rmse:0.056204\tvalidation_1-rmse:0.056204\n",
            "[168]\tvalidation_0-rmse:0.05575\tvalidation_1-rmse:0.05575\n",
            "[169]\tvalidation_0-rmse:0.055301\tvalidation_1-rmse:0.055301\n",
            "[170]\tvalidation_0-rmse:0.054857\tvalidation_1-rmse:0.054857\n",
            "[171]\tvalidation_0-rmse:0.054416\tvalidation_1-rmse:0.054416\n",
            "[172]\tvalidation_0-rmse:0.053979\tvalidation_1-rmse:0.053979\n",
            "[173]\tvalidation_0-rmse:0.053548\tvalidation_1-rmse:0.053548\n",
            "[174]\tvalidation_0-rmse:0.05312\tvalidation_1-rmse:0.05312\n",
            "[175]\tvalidation_0-rmse:0.052696\tvalidation_1-rmse:0.052696\n",
            "[176]\tvalidation_0-rmse:0.052277\tvalidation_1-rmse:0.052277\n",
            "[177]\tvalidation_0-rmse:0.051862\tvalidation_1-rmse:0.051862\n",
            "[178]\tvalidation_0-rmse:0.05145\tvalidation_1-rmse:0.05145\n",
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            "[180]\tvalidation_0-rmse:0.05064\tvalidation_1-rmse:0.05064\n",
            "[181]\tvalidation_0-rmse:0.050241\tvalidation_1-rmse:0.050241\n",
            "[182]\tvalidation_0-rmse:0.049845\tvalidation_1-rmse:0.049845\n",
            "[183]\tvalidation_0-rmse:0.049455\tvalidation_1-rmse:0.049455\n",
            "[184]\tvalidation_0-rmse:0.049068\tvalidation_1-rmse:0.049068\n",
            "[185]\tvalidation_0-rmse:0.048684\tvalidation_1-rmse:0.048684\n",
            "[186]\tvalidation_0-rmse:0.048305\tvalidation_1-rmse:0.048305\n",
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            "[190]\tvalidation_0-rmse:0.046824\tvalidation_1-rmse:0.046824\n",
            "[191]\tvalidation_0-rmse:0.046462\tvalidation_1-rmse:0.046462\n",
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            "[193]\tvalidation_0-rmse:0.045751\tvalidation_1-rmse:0.045751\n",
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            "[896]\tvalidation_0-rmse:0.009046\tvalidation_1-rmse:0.009046\n",
            "[897]\tvalidation_0-rmse:0.009036\tvalidation_1-rmse:0.009036\n",
            "[898]\tvalidation_0-rmse:0.009025\tvalidation_1-rmse:0.009025\n",
            "[899]\tvalidation_0-rmse:0.009015\tvalidation_1-rmse:0.009015\n",
            "[900]\tvalidation_0-rmse:0.00901\tvalidation_1-rmse:0.00901\n",
            "[901]\tvalidation_0-rmse:0.009002\tvalidation_1-rmse:0.009002\n",
            "[902]\tvalidation_0-rmse:0.008995\tvalidation_1-rmse:0.008995\n",
            "[903]\tvalidation_0-rmse:0.008991\tvalidation_1-rmse:0.008991\n",
            "[904]\tvalidation_0-rmse:0.008982\tvalidation_1-rmse:0.008982\n",
            "[905]\tvalidation_0-rmse:0.008978\tvalidation_1-rmse:0.008978\n",
            "[906]\tvalidation_0-rmse:0.008967\tvalidation_1-rmse:0.008967\n",
            "[907]\tvalidation_0-rmse:0.008963\tvalidation_1-rmse:0.008963\n",
            "[908]\tvalidation_0-rmse:0.008952\tvalidation_1-rmse:0.008952\n",
            "[909]\tvalidation_0-rmse:0.008949\tvalidation_1-rmse:0.008949\n",
            "[910]\tvalidation_0-rmse:0.00894\tvalidation_1-rmse:0.00894\n",
            "[911]\tvalidation_0-rmse:0.008932\tvalidation_1-rmse:0.008932\n",
            "[912]\tvalidation_0-rmse:0.008928\tvalidation_1-rmse:0.008928\n",
            "[913]\tvalidation_0-rmse:0.008924\tvalidation_1-rmse:0.008924\n",
            "[914]\tvalidation_0-rmse:0.008917\tvalidation_1-rmse:0.008917\n",
            "[915]\tvalidation_0-rmse:0.008913\tvalidation_1-rmse:0.008913\n",
            "[916]\tvalidation_0-rmse:0.008902\tvalidation_1-rmse:0.008902\n",
            "[917]\tvalidation_0-rmse:0.008893\tvalidation_1-rmse:0.008893\n",
            "[918]\tvalidation_0-rmse:0.00889\tvalidation_1-rmse:0.00889\n",
            "[919]\tvalidation_0-rmse:0.00888\tvalidation_1-rmse:0.00888\n",
            "[920]\tvalidation_0-rmse:0.008871\tvalidation_1-rmse:0.008871\n",
            "[921]\tvalidation_0-rmse:0.008867\tvalidation_1-rmse:0.008867\n",
            "[922]\tvalidation_0-rmse:0.008863\tvalidation_1-rmse:0.008863\n",
            "[923]\tvalidation_0-rmse:0.008856\tvalidation_1-rmse:0.008856\n",
            "[924]\tvalidation_0-rmse:0.008852\tvalidation_1-rmse:0.008852\n",
            "[925]\tvalidation_0-rmse:0.008842\tvalidation_1-rmse:0.008842\n",
            "[926]\tvalidation_0-rmse:0.008834\tvalidation_1-rmse:0.008834\n",
            "[927]\tvalidation_0-rmse:0.008824\tvalidation_1-rmse:0.008824\n",
            "[928]\tvalidation_0-rmse:0.00882\tvalidation_1-rmse:0.00882\n",
            "[929]\tvalidation_0-rmse:0.008813\tvalidation_1-rmse:0.008813\n",
            "[930]\tvalidation_0-rmse:0.008809\tvalidation_1-rmse:0.008809\n",
            "[931]\tvalidation_0-rmse:0.008806\tvalidation_1-rmse:0.008806\n",
            "[932]\tvalidation_0-rmse:0.008796\tvalidation_1-rmse:0.008796\n",
            "[933]\tvalidation_0-rmse:0.008789\tvalidation_1-rmse:0.008789\n",
            "[934]\tvalidation_0-rmse:0.008785\tvalidation_1-rmse:0.008785\n",
            "[935]\tvalidation_0-rmse:0.008781\tvalidation_1-rmse:0.008781\n",
            "[936]\tvalidation_0-rmse:0.008773\tvalidation_1-rmse:0.008773\n",
            "[937]\tvalidation_0-rmse:0.008768\tvalidation_1-rmse:0.008768\n",
            "[938]\tvalidation_0-rmse:0.008761\tvalidation_1-rmse:0.008761\n",
            "[939]\tvalidation_0-rmse:0.008757\tvalidation_1-rmse:0.008757\n",
            "[940]\tvalidation_0-rmse:0.008753\tvalidation_1-rmse:0.008753\n",
            "[941]\tvalidation_0-rmse:0.008746\tvalidation_1-rmse:0.008746\n",
            "[942]\tvalidation_0-rmse:0.008743\tvalidation_1-rmse:0.008743\n",
            "[943]\tvalidation_0-rmse:0.008733\tvalidation_1-rmse:0.008733\n",
            "[944]\tvalidation_0-rmse:0.008729\tvalidation_1-rmse:0.008729\n",
            "[945]\tvalidation_0-rmse:0.008725\tvalidation_1-rmse:0.008725\n",
            "[946]\tvalidation_0-rmse:0.008715\tvalidation_1-rmse:0.008715\n",
            "[947]\tvalidation_0-rmse:0.008707\tvalidation_1-rmse:0.008707\n",
            "[948]\tvalidation_0-rmse:0.008697\tvalidation_1-rmse:0.008697\n",
            "[949]\tvalidation_0-rmse:0.008694\tvalidation_1-rmse:0.008694\n",
            "[950]\tvalidation_0-rmse:0.008685\tvalidation_1-rmse:0.008685\n",
            "[951]\tvalidation_0-rmse:0.008679\tvalidation_1-rmse:0.008679\n",
            "[952]\tvalidation_0-rmse:0.008675\tvalidation_1-rmse:0.008675\n",
            "[953]\tvalidation_0-rmse:0.008671\tvalidation_1-rmse:0.008671\n",
            "[954]\tvalidation_0-rmse:0.008663\tvalidation_1-rmse:0.008663\n",
            "[955]\tvalidation_0-rmse:0.008653\tvalidation_1-rmse:0.008653\n",
            "[956]\tvalidation_0-rmse:0.00865\tvalidation_1-rmse:0.00865\n",
            "[957]\tvalidation_0-rmse:0.008642\tvalidation_1-rmse:0.008642\n",
            "[958]\tvalidation_0-rmse:0.008637\tvalidation_1-rmse:0.008637\n",
            "[959]\tvalidation_0-rmse:0.008629\tvalidation_1-rmse:0.008629\n",
            "[960]\tvalidation_0-rmse:0.008625\tvalidation_1-rmse:0.008625\n",
            "[961]\tvalidation_0-rmse:0.008618\tvalidation_1-rmse:0.008618\n",
            "[962]\tvalidation_0-rmse:0.008615\tvalidation_1-rmse:0.008615\n",
            "[963]\tvalidation_0-rmse:0.008606\tvalidation_1-rmse:0.008606\n",
            "[964]\tvalidation_0-rmse:0.008599\tvalidation_1-rmse:0.008599\n",
            "[965]\tvalidation_0-rmse:0.008596\tvalidation_1-rmse:0.008596\n",
            "[966]\tvalidation_0-rmse:0.008592\tvalidation_1-rmse:0.008592\n",
            "[967]\tvalidation_0-rmse:0.008584\tvalidation_1-rmse:0.008584\n",
            "[968]\tvalidation_0-rmse:0.008575\tvalidation_1-rmse:0.008575\n",
            "[969]\tvalidation_0-rmse:0.008565\tvalidation_1-rmse:0.008565\n",
            "[970]\tvalidation_0-rmse:0.008559\tvalidation_1-rmse:0.008559\n",
            "[971]\tvalidation_0-rmse:0.008556\tvalidation_1-rmse:0.008556\n",
            "[972]\tvalidation_0-rmse:0.008552\tvalidation_1-rmse:0.008552\n",
            "[973]\tvalidation_0-rmse:0.008544\tvalidation_1-rmse:0.008544\n",
            "[974]\tvalidation_0-rmse:0.008538\tvalidation_1-rmse:0.008538\n",
            "[975]\tvalidation_0-rmse:0.008534\tvalidation_1-rmse:0.008534\n",
            "[976]\tvalidation_0-rmse:0.008525\tvalidation_1-rmse:0.008525\n",
            "[977]\tvalidation_0-rmse:0.008519\tvalidation_1-rmse:0.008519\n",
            "[978]\tvalidation_0-rmse:0.008514\tvalidation_1-rmse:0.008514\n",
            "[979]\tvalidation_0-rmse:0.008506\tvalidation_1-rmse:0.008506\n",
            "[980]\tvalidation_0-rmse:0.008498\tvalidation_1-rmse:0.008498\n",
            "[981]\tvalidation_0-rmse:0.008495\tvalidation_1-rmse:0.008495\n",
            "[982]\tvalidation_0-rmse:0.008485\tvalidation_1-rmse:0.008485\n",
            "[983]\tvalidation_0-rmse:0.008477\tvalidation_1-rmse:0.008477\n",
            "[984]\tvalidation_0-rmse:0.00847\tvalidation_1-rmse:0.00847\n",
            "[985]\tvalidation_0-rmse:0.008466\tvalidation_1-rmse:0.008466\n",
            "[986]\tvalidation_0-rmse:0.008462\tvalidation_1-rmse:0.008462\n",
            "[987]\tvalidation_0-rmse:0.008454\tvalidation_1-rmse:0.008454\n",
            "[988]\tvalidation_0-rmse:0.008451\tvalidation_1-rmse:0.008451\n",
            "[989]\tvalidation_0-rmse:0.008444\tvalidation_1-rmse:0.008444\n",
            "[990]\tvalidation_0-rmse:0.00844\tvalidation_1-rmse:0.00844\n",
            "[991]\tvalidation_0-rmse:0.008435\tvalidation_1-rmse:0.008435\n",
            "[992]\tvalidation_0-rmse:0.008429\tvalidation_1-rmse:0.008429\n",
            "[993]\tvalidation_0-rmse:0.008421\tvalidation_1-rmse:0.008421\n",
            "[994]\tvalidation_0-rmse:0.008414\tvalidation_1-rmse:0.008414\n",
            "[995]\tvalidation_0-rmse:0.008405\tvalidation_1-rmse:0.008405\n",
            "[996]\tvalidation_0-rmse:0.008399\tvalidation_1-rmse:0.008399\n",
            "[997]\tvalidation_0-rmse:0.008396\tvalidation_1-rmse:0.008396\n",
            "[998]\tvalidation_0-rmse:0.008393\tvalidation_1-rmse:0.008393\n",
            "[999]\tvalidation_0-rmse:0.008386\tvalidation_1-rmse:0.008386\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "XGBRegressor(learning_rate=0.01, n_estimators=1000)"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,8))\n",
        "feature_importance = plot_importance(xgb, height=0.9)\n",
        "feature_importance"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 330
        },
        "id": "DkS9xkypRXEb",
        "outputId": "6cdada65-f612-4777-805e-5c7c7e85f1c1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f9be5d01090>"
            ]
          },
          "metadata": {},
          "execution_count": 25
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x576 with 0 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "predicted_results_v = xgb.predict(X_valid3)\n",
        "predicted_results_t = xgb.predict(X_train3)\n",
        "predicted_results_v= predicted_results_v.reshape(-1, 1)\n",
        "predicted_results_t= predicted_results_t.reshape(-1, 1)\n",
        "predicted_results_v = scaler1.inverse_transform(predicted_results_v)\n",
        "predicted_results_t = scaler.inverse_transform(predicted_results_t)"
      ],
      "metadata": {
        "id": "zCIStuEIRaay"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(20,15))\n",
        "plt.plot(X_train2.index,list(y_trainn),label=\"actual Price train\",color='b')\n",
        "plt.plot(X_train2.index,list(predicted_results_t),label=\"predicted Price train\",color='r')\n",
        "plt.plot(X_valid2.index,list(y_validn),label=\"actual Price valid\",color='m')\n",
        "plt.plot(X_valid2.index,list(predicted_results_v),label=\"predicted Price valid\",color='g')\n",
        "\n",
        "plt.xlabel('Date')\n",
        "plt.ylabel('Nifty 50 Closing Price')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 826
        },
        "id": "MINyxmafRe5U",
        "outputId": "a0f59a73-6846-4873-9f18-700124096475"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x1080 with 1 Axes>"
            ],
            "image/png": 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    },
    {
      "cell_type": "code",
      "source": [
        "xgb = XGBRegressor(n_estimators=1000,learning_rate=0.0099,max_depth=15)\n",
        "xgb\n",
        "\n",
        "xgb.fit(X_train3,y_train1,\n",
        "        eval_set=[(X_train3,y_train1),(X_valid3,y_valid1)],\n",
        "        early_stopping_rounds=100,\n",
        "        verbose=True) # Change verbose to True if you want to see it train"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Nmr1kGSJRmZf",
        "outputId": "e7a72120-cb94-4c88-b540-d2bfa7f4864d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[16:08:07] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
            "[0]\tvalidation_0-rmse:0.246272\tvalidation_1-rmse:0.246272\n",
            "Multiple eval metrics have been passed: 'validation_1-rmse' will be used for early stopping.\n",
            "\n",
            "Will train until validation_1-rmse hasn't improved in 100 rounds.\n",
            "[1]\tvalidation_0-rmse:0.24401\tvalidation_1-rmse:0.24401\n",
            "[2]\tvalidation_0-rmse:0.241769\tvalidation_1-rmse:0.241769\n",
            "[3]\tvalidation_0-rmse:0.23955\tvalidation_1-rmse:0.23955\n",
            "[4]\tvalidation_0-rmse:0.237352\tvalidation_1-rmse:0.237352\n",
            "[5]\tvalidation_0-rmse:0.235176\tvalidation_1-rmse:0.235176\n",
            "[6]\tvalidation_0-rmse:0.233019\tvalidation_1-rmse:0.233019\n",
            "[7]\tvalidation_0-rmse:0.230884\tvalidation_1-rmse:0.230884\n",
            "[8]\tvalidation_0-rmse:0.228771\tvalidation_1-rmse:0.228771\n",
            "[9]\tvalidation_0-rmse:0.226672\tvalidation_1-rmse:0.226672\n",
            "[10]\tvalidation_0-rmse:0.224597\tvalidation_1-rmse:0.224597\n",
            "[11]\tvalidation_0-rmse:0.222539\tvalidation_1-rmse:0.222539\n",
            "[12]\tvalidation_0-rmse:0.220503\tvalidation_1-rmse:0.220503\n",
            "[13]\tvalidation_0-rmse:0.218484\tvalidation_1-rmse:0.218484\n",
            "[14]\tvalidation_0-rmse:0.216486\tvalidation_1-rmse:0.216486\n",
            "[15]\tvalidation_0-rmse:0.214506\tvalidation_1-rmse:0.214506\n",
            "[16]\tvalidation_0-rmse:0.212546\tvalidation_1-rmse:0.212546\n",
            "[17]\tvalidation_0-rmse:0.210602\tvalidation_1-rmse:0.210602\n",
            "[18]\tvalidation_0-rmse:0.20868\tvalidation_1-rmse:0.20868\n",
            "[19]\tvalidation_0-rmse:0.206775\tvalidation_1-rmse:0.206775\n",
            "[20]\tvalidation_0-rmse:0.204889\tvalidation_1-rmse:0.204889\n",
            "[21]\tvalidation_0-rmse:0.203019\tvalidation_1-rmse:0.203019\n",
            "[22]\tvalidation_0-rmse:0.20117\tvalidation_1-rmse:0.20117\n",
            "[23]\tvalidation_0-rmse:0.199337\tvalidation_1-rmse:0.199337\n",
            "[24]\tvalidation_0-rmse:0.197522\tvalidation_1-rmse:0.197522\n",
            "[25]\tvalidation_0-rmse:0.195724\tvalidation_1-rmse:0.195724\n",
            "[26]\tvalidation_0-rmse:0.193944\tvalidation_1-rmse:0.193944\n",
            "[27]\tvalidation_0-rmse:0.19218\tvalidation_1-rmse:0.19218\n",
            "[28]\tvalidation_0-rmse:0.190434\tvalidation_1-rmse:0.190434\n",
            "[29]\tvalidation_0-rmse:0.188705\tvalidation_1-rmse:0.188705\n",
            "[30]\tvalidation_0-rmse:0.186992\tvalidation_1-rmse:0.186992\n",
            "[31]\tvalidation_0-rmse:0.185294\tvalidation_1-rmse:0.185294\n",
            "[32]\tvalidation_0-rmse:0.183614\tvalidation_1-rmse:0.183614\n",
            "[33]\tvalidation_0-rmse:0.181949\tvalidation_1-rmse:0.181949\n",
            "[34]\tvalidation_0-rmse:0.180301\tvalidation_1-rmse:0.180301\n",
            "[35]\tvalidation_0-rmse:0.178665\tvalidation_1-rmse:0.178665\n",
            "[36]\tvalidation_0-rmse:0.177048\tvalidation_1-rmse:0.177048\n",
            "[37]\tvalidation_0-rmse:0.175443\tvalidation_1-rmse:0.175443\n",
            "[38]\tvalidation_0-rmse:0.173856\tvalidation_1-rmse:0.173856\n",
            "[39]\tvalidation_0-rmse:0.172284\tvalidation_1-rmse:0.172284\n",
            "[40]\tvalidation_0-rmse:0.170727\tvalidation_1-rmse:0.170727\n",
            "[41]\tvalidation_0-rmse:0.169183\tvalidation_1-rmse:0.169183\n",
            "[42]\tvalidation_0-rmse:0.167654\tvalidation_1-rmse:0.167654\n",
            "[43]\tvalidation_0-rmse:0.166136\tvalidation_1-rmse:0.166136\n",
            "[44]\tvalidation_0-rmse:0.164637\tvalidation_1-rmse:0.164637\n",
            "[45]\tvalidation_0-rmse:0.163148\tvalidation_1-rmse:0.163148\n",
            "[46]\tvalidation_0-rmse:0.161673\tvalidation_1-rmse:0.161673\n",
            "[47]\tvalidation_0-rmse:0.160215\tvalidation_1-rmse:0.160215\n",
            "[48]\tvalidation_0-rmse:0.158768\tvalidation_1-rmse:0.158768\n",
            "[49]\tvalidation_0-rmse:0.157333\tvalidation_1-rmse:0.157333\n",
            "[50]\tvalidation_0-rmse:0.155918\tvalidation_1-rmse:0.155918\n",
            "[51]\tvalidation_0-rmse:0.154512\tvalidation_1-rmse:0.154512\n",
            "[52]\tvalidation_0-rmse:0.15312\tvalidation_1-rmse:0.15312\n",
            "[53]\tvalidation_0-rmse:0.151742\tvalidation_1-rmse:0.151742\n",
            "[54]\tvalidation_0-rmse:0.150377\tvalidation_1-rmse:0.150377\n",
            "[55]\tvalidation_0-rmse:0.149025\tvalidation_1-rmse:0.149025\n",
            "[56]\tvalidation_0-rmse:0.147687\tvalidation_1-rmse:0.147687\n",
            "[57]\tvalidation_0-rmse:0.146359\tvalidation_1-rmse:0.146359\n",
            "[58]\tvalidation_0-rmse:0.145044\tvalidation_1-rmse:0.145044\n",
            "[59]\tvalidation_0-rmse:0.143742\tvalidation_1-rmse:0.143742\n",
            "[60]\tvalidation_0-rmse:0.142454\tvalidation_1-rmse:0.142454\n",
            "[61]\tvalidation_0-rmse:0.141175\tvalidation_1-rmse:0.141175\n",
            "[62]\tvalidation_0-rmse:0.139909\tvalidation_1-rmse:0.139909\n",
            "[63]\tvalidation_0-rmse:0.138655\tvalidation_1-rmse:0.138655\n",
            "[64]\tvalidation_0-rmse:0.137412\tvalidation_1-rmse:0.137412\n",
            "[65]\tvalidation_0-rmse:0.136181\tvalidation_1-rmse:0.136181\n",
            "[66]\tvalidation_0-rmse:0.134962\tvalidation_1-rmse:0.134962\n",
            "[67]\tvalidation_0-rmse:0.133754\tvalidation_1-rmse:0.133754\n",
            "[68]\tvalidation_0-rmse:0.132556\tvalidation_1-rmse:0.132556\n",
            "[69]\tvalidation_0-rmse:0.131371\tvalidation_1-rmse:0.131371\n",
            "[70]\tvalidation_0-rmse:0.130195\tvalidation_1-rmse:0.130195\n",
            "[71]\tvalidation_0-rmse:0.129034\tvalidation_1-rmse:0.129034\n",
            "[72]\tvalidation_0-rmse:0.127881\tvalidation_1-rmse:0.127881\n",
            "[73]\tvalidation_0-rmse:0.126739\tvalidation_1-rmse:0.126739\n",
            "[74]\tvalidation_0-rmse:0.125609\tvalidation_1-rmse:0.125609\n",
            "[75]\tvalidation_0-rmse:0.12449\tvalidation_1-rmse:0.12449\n",
            "[76]\tvalidation_0-rmse:0.12338\tvalidation_1-rmse:0.12338\n",
            "[77]\tvalidation_0-rmse:0.122281\tvalidation_1-rmse:0.122281\n",
            "[78]\tvalidation_0-rmse:0.121194\tvalidation_1-rmse:0.121194\n",
            "[79]\tvalidation_0-rmse:0.120116\tvalidation_1-rmse:0.120116\n",
            "[80]\tvalidation_0-rmse:0.119049\tvalidation_1-rmse:0.119049\n",
            "[81]\tvalidation_0-rmse:0.117992\tvalidation_1-rmse:0.117992\n",
            "[82]\tvalidation_0-rmse:0.116944\tvalidation_1-rmse:0.116944\n",
            "[83]\tvalidation_0-rmse:0.115907\tvalidation_1-rmse:0.115907\n",
            "[84]\tvalidation_0-rmse:0.11488\tvalidation_1-rmse:0.11488\n",
            "[85]\tvalidation_0-rmse:0.113863\tvalidation_1-rmse:0.113863\n",
            "[86]\tvalidation_0-rmse:0.112855\tvalidation_1-rmse:0.112855\n",
            "[87]\tvalidation_0-rmse:0.111858\tvalidation_1-rmse:0.111858\n",
            "[88]\tvalidation_0-rmse:0.110867\tvalidation_1-rmse:0.110867\n",
            "[89]\tvalidation_0-rmse:0.109889\tvalidation_1-rmse:0.109889\n",
            "[90]\tvalidation_0-rmse:0.108918\tvalidation_1-rmse:0.108918\n",
            "[91]\tvalidation_0-rmse:0.107957\tvalidation_1-rmse:0.107957\n",
            "[92]\tvalidation_0-rmse:0.107006\tvalidation_1-rmse:0.107006\n",
            "[93]\tvalidation_0-rmse:0.106063\tvalidation_1-rmse:0.106063\n",
            "[94]\tvalidation_0-rmse:0.105128\tvalidation_1-rmse:0.105128\n",
            "[95]\tvalidation_0-rmse:0.104203\tvalidation_1-rmse:0.104203\n",
            "[96]\tvalidation_0-rmse:0.103287\tvalidation_1-rmse:0.103287\n",
            "[97]\tvalidation_0-rmse:0.102378\tvalidation_1-rmse:0.102378\n",
            "[98]\tvalidation_0-rmse:0.101478\tvalidation_1-rmse:0.101478\n",
            "[99]\tvalidation_0-rmse:0.100586\tvalidation_1-rmse:0.100586\n",
            "[100]\tvalidation_0-rmse:0.099703\tvalidation_1-rmse:0.099703\n",
            "[101]\tvalidation_0-rmse:0.098827\tvalidation_1-rmse:0.098827\n",
            "[102]\tvalidation_0-rmse:0.09796\tvalidation_1-rmse:0.09796\n",
            "[103]\tvalidation_0-rmse:0.0971\tvalidation_1-rmse:0.0971\n",
            "[104]\tvalidation_0-rmse:0.096248\tvalidation_1-rmse:0.096248\n",
            "[105]\tvalidation_0-rmse:0.095405\tvalidation_1-rmse:0.095405\n",
            "[106]\tvalidation_0-rmse:0.094568\tvalidation_1-rmse:0.094568\n",
            "[107]\tvalidation_0-rmse:0.093739\tvalidation_1-rmse:0.093739\n",
            "[108]\tvalidation_0-rmse:0.092919\tvalidation_1-rmse:0.092919\n",
            "[109]\tvalidation_0-rmse:0.092105\tvalidation_1-rmse:0.092105\n",
            "[110]\tvalidation_0-rmse:0.0913\tvalidation_1-rmse:0.0913\n",
            "[111]\tvalidation_0-rmse:0.090502\tvalidation_1-rmse:0.090502\n",
            "[112]\tvalidation_0-rmse:0.089711\tvalidation_1-rmse:0.089711\n",
            "[113]\tvalidation_0-rmse:0.088927\tvalidation_1-rmse:0.088927\n",
            "[114]\tvalidation_0-rmse:0.088149\tvalidation_1-rmse:0.088149\n",
            "[115]\tvalidation_0-rmse:0.08738\tvalidation_1-rmse:0.08738\n",
            "[116]\tvalidation_0-rmse:0.086618\tvalidation_1-rmse:0.086618\n",
            "[117]\tvalidation_0-rmse:0.085863\tvalidation_1-rmse:0.085863\n",
            "[118]\tvalidation_0-rmse:0.085115\tvalidation_1-rmse:0.085115\n",
            "[119]\tvalidation_0-rmse:0.084375\tvalidation_1-rmse:0.084375\n",
            "[120]\tvalidation_0-rmse:0.083641\tvalidation_1-rmse:0.083641\n",
            "[121]\tvalidation_0-rmse:0.082913\tvalidation_1-rmse:0.082913\n",
            "[122]\tvalidation_0-rmse:0.082193\tvalidation_1-rmse:0.082193\n",
            "[123]\tvalidation_0-rmse:0.081478\tvalidation_1-rmse:0.081478\n",
            "[124]\tvalidation_0-rmse:0.08077\tvalidation_1-rmse:0.08077\n",
            "[125]\tvalidation_0-rmse:0.080069\tvalidation_1-rmse:0.080069\n",
            "[126]\tvalidation_0-rmse:0.079375\tvalidation_1-rmse:0.079375\n",
            "[127]\tvalidation_0-rmse:0.078687\tvalidation_1-rmse:0.078687\n",
            "[128]\tvalidation_0-rmse:0.078006\tvalidation_1-rmse:0.078006\n",
            "[129]\tvalidation_0-rmse:0.077331\tvalidation_1-rmse:0.077331\n",
            "[130]\tvalidation_0-rmse:0.076661\tvalidation_1-rmse:0.076661\n",
            "[131]\tvalidation_0-rmse:0.075999\tvalidation_1-rmse:0.075999\n",
            "[132]\tvalidation_0-rmse:0.075342\tvalidation_1-rmse:0.075342\n",
            "[133]\tvalidation_0-rmse:0.074691\tvalidation_1-rmse:0.074691\n",
            "[134]\tvalidation_0-rmse:0.074047\tvalidation_1-rmse:0.074047\n",
            "[135]\tvalidation_0-rmse:0.073409\tvalidation_1-rmse:0.073409\n",
            "[136]\tvalidation_0-rmse:0.072776\tvalidation_1-rmse:0.072776\n",
            "[137]\tvalidation_0-rmse:0.07215\tvalidation_1-rmse:0.07215\n",
            "[138]\tvalidation_0-rmse:0.071529\tvalidation_1-rmse:0.071529\n",
            "[139]\tvalidation_0-rmse:0.070914\tvalidation_1-rmse:0.070914\n",
            "[140]\tvalidation_0-rmse:0.070305\tvalidation_1-rmse:0.070305\n",
            "[141]\tvalidation_0-rmse:0.0697\tvalidation_1-rmse:0.0697\n",
            "[142]\tvalidation_0-rmse:0.069102\tvalidation_1-rmse:0.069102\n",
            "[143]\tvalidation_0-rmse:0.068509\tvalidation_1-rmse:0.068509\n",
            "[144]\tvalidation_0-rmse:0.067921\tvalidation_1-rmse:0.067921\n",
            "[145]\tvalidation_0-rmse:0.067339\tvalidation_1-rmse:0.067339\n",
            "[146]\tvalidation_0-rmse:0.066762\tvalidation_1-rmse:0.066762\n",
            "[147]\tvalidation_0-rmse:0.066191\tvalidation_1-rmse:0.066191\n",
            "[148]\tvalidation_0-rmse:0.065625\tvalidation_1-rmse:0.065625\n",
            "[149]\tvalidation_0-rmse:0.065064\tvalidation_1-rmse:0.065064\n",
            "[150]\tvalidation_0-rmse:0.064508\tvalidation_1-rmse:0.064508\n",
            "[151]\tvalidation_0-rmse:0.063957\tvalidation_1-rmse:0.063957\n",
            "[152]\tvalidation_0-rmse:0.063412\tvalidation_1-rmse:0.063412\n",
            "[153]\tvalidation_0-rmse:0.062872\tvalidation_1-rmse:0.062872\n",
            "[154]\tvalidation_0-rmse:0.062336\tvalidation_1-rmse:0.062336\n",
            "[155]\tvalidation_0-rmse:0.061805\tvalidation_1-rmse:0.061805\n",
            "[156]\tvalidation_0-rmse:0.061279\tvalidation_1-rmse:0.061279\n",
            "[157]\tvalidation_0-rmse:0.060758\tvalidation_1-rmse:0.060758\n",
            "[158]\tvalidation_0-rmse:0.060243\tvalidation_1-rmse:0.060243\n",
            "[159]\tvalidation_0-rmse:0.05973\tvalidation_1-rmse:0.05973\n",
            "[160]\tvalidation_0-rmse:0.059223\tvalidation_1-rmse:0.059223\n",
            "[161]\tvalidation_0-rmse:0.058721\tvalidation_1-rmse:0.058721\n",
            "[162]\tvalidation_0-rmse:0.058224\tvalidation_1-rmse:0.058224\n",
            "[163]\tvalidation_0-rmse:0.057732\tvalidation_1-rmse:0.057732\n",
            "[164]\tvalidation_0-rmse:0.057244\tvalidation_1-rmse:0.057244\n",
            "[165]\tvalidation_0-rmse:0.05676\tvalidation_1-rmse:0.05676\n",
            "[166]\tvalidation_0-rmse:0.056281\tvalidation_1-rmse:0.056281\n",
            "[167]\tvalidation_0-rmse:0.055806\tvalidation_1-rmse:0.055806\n",
            "[168]\tvalidation_0-rmse:0.055336\tvalidation_1-rmse:0.055336\n",
            "[169]\tvalidation_0-rmse:0.05487\tvalidation_1-rmse:0.05487\n",
            "[170]\tvalidation_0-rmse:0.054408\tvalidation_1-rmse:0.054408\n",
            "[171]\tvalidation_0-rmse:0.053951\tvalidation_1-rmse:0.053951\n",
            "[172]\tvalidation_0-rmse:0.053498\tvalidation_1-rmse:0.053498\n",
            "[173]\tvalidation_0-rmse:0.053049\tvalidation_1-rmse:0.053049\n",
            "[174]\tvalidation_0-rmse:0.052603\tvalidation_1-rmse:0.052603\n",
            "[175]\tvalidation_0-rmse:0.052162\tvalidation_1-rmse:0.052162\n",
            "[176]\tvalidation_0-rmse:0.051726\tvalidation_1-rmse:0.051726\n",
            "[177]\tvalidation_0-rmse:0.051293\tvalidation_1-rmse:0.051293\n",
            "[178]\tvalidation_0-rmse:0.050862\tvalidation_1-rmse:0.050862\n",
            "[179]\tvalidation_0-rmse:0.050437\tvalidation_1-rmse:0.050437\n",
            "[180]\tvalidation_0-rmse:0.050015\tvalidation_1-rmse:0.050015\n",
            "[181]\tvalidation_0-rmse:0.049595\tvalidation_1-rmse:0.049595\n",
            "[182]\tvalidation_0-rmse:0.04918\tvalidation_1-rmse:0.04918\n",
            "[183]\tvalidation_0-rmse:0.048768\tvalidation_1-rmse:0.048768\n",
            "[184]\tvalidation_0-rmse:0.048361\tvalidation_1-rmse:0.048361\n",
            "[185]\tvalidation_0-rmse:0.047958\tvalidation_1-rmse:0.047958\n",
            "[186]\tvalidation_0-rmse:0.047558\tvalidation_1-rmse:0.047558\n",
            "[187]\tvalidation_0-rmse:0.047163\tvalidation_1-rmse:0.047163\n",
            "[188]\tvalidation_0-rmse:0.04677\tvalidation_1-rmse:0.04677\n",
            "[189]\tvalidation_0-rmse:0.046381\tvalidation_1-rmse:0.046381\n",
            "[190]\tvalidation_0-rmse:0.045995\tvalidation_1-rmse:0.045995\n",
            "[191]\tvalidation_0-rmse:0.045614\tvalidation_1-rmse:0.045614\n",
            "[192]\tvalidation_0-rmse:0.045235\tvalidation_1-rmse:0.045235\n",
            "[193]\tvalidation_0-rmse:0.04486\tvalidation_1-rmse:0.04486\n",
            "[194]\tvalidation_0-rmse:0.044488\tvalidation_1-rmse:0.044488\n",
            "[195]\tvalidation_0-rmse:0.044119\tvalidation_1-rmse:0.044119\n",
            "[196]\tvalidation_0-rmse:0.043753\tvalidation_1-rmse:0.043753\n",
            "[197]\tvalidation_0-rmse:0.043391\tvalidation_1-rmse:0.043391\n",
            "[198]\tvalidation_0-rmse:0.04303\tvalidation_1-rmse:0.04303\n",
            "[199]\tvalidation_0-rmse:0.042674\tvalidation_1-rmse:0.042674\n",
            "[200]\tvalidation_0-rmse:0.04232\tvalidation_1-rmse:0.04232\n",
            "[201]\tvalidation_0-rmse:0.041971\tvalidation_1-rmse:0.041971\n",
            "[202]\tvalidation_0-rmse:0.041624\tvalidation_1-rmse:0.041624\n",
            "[203]\tvalidation_0-rmse:0.04128\tvalidation_1-rmse:0.04128\n",
            "[204]\tvalidation_0-rmse:0.040939\tvalidation_1-rmse:0.040939\n",
            "[205]\tvalidation_0-rmse:0.040601\tvalidation_1-rmse:0.040601\n",
            "[206]\tvalidation_0-rmse:0.040266\tvalidation_1-rmse:0.040266\n",
            "[207]\tvalidation_0-rmse:0.039935\tvalidation_1-rmse:0.039935\n",
            "[208]\tvalidation_0-rmse:0.039605\tvalidation_1-rmse:0.039605\n",
            "[209]\tvalidation_0-rmse:0.039279\tvalidation_1-rmse:0.039279\n",
            "[210]\tvalidation_0-rmse:0.038956\tvalidation_1-rmse:0.038956\n",
            "[211]\tvalidation_0-rmse:0.038636\tvalidation_1-rmse:0.038636\n",
            "[212]\tvalidation_0-rmse:0.038319\tvalidation_1-rmse:0.038319\n",
            "[213]\tvalidation_0-rmse:0.038005\tvalidation_1-rmse:0.038005\n",
            "[214]\tvalidation_0-rmse:0.037693\tvalidation_1-rmse:0.037693\n",
            "[215]\tvalidation_0-rmse:0.037384\tvalidation_1-rmse:0.037384\n",
            "[216]\tvalidation_0-rmse:0.037079\tvalidation_1-rmse:0.037079\n",
            "[217]\tvalidation_0-rmse:0.036776\tvalidation_1-rmse:0.036776\n",
            "[218]\tvalidation_0-rmse:0.036476\tvalidation_1-rmse:0.036476\n",
            "[219]\tvalidation_0-rmse:0.036179\tvalidation_1-rmse:0.036179\n",
            "[220]\tvalidation_0-rmse:0.035885\tvalidation_1-rmse:0.035885\n",
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            "[927]\tvalidation_0-rmse:0.000627\tvalidation_1-rmse:0.000627\n",
            "[928]\tvalidation_0-rmse:0.000626\tvalidation_1-rmse:0.000626\n",
            "[929]\tvalidation_0-rmse:0.000625\tvalidation_1-rmse:0.000625\n",
            "[930]\tvalidation_0-rmse:0.000623\tvalidation_1-rmse:0.000623\n",
            "[931]\tvalidation_0-rmse:0.000622\tvalidation_1-rmse:0.000622\n",
            "[932]\tvalidation_0-rmse:0.000621\tvalidation_1-rmse:0.000621\n",
            "[933]\tvalidation_0-rmse:0.000619\tvalidation_1-rmse:0.000619\n",
            "[934]\tvalidation_0-rmse:0.000617\tvalidation_1-rmse:0.000617\n",
            "[935]\tvalidation_0-rmse:0.000616\tvalidation_1-rmse:0.000616\n",
            "[936]\tvalidation_0-rmse:0.000615\tvalidation_1-rmse:0.000615\n",
            "[937]\tvalidation_0-rmse:0.000614\tvalidation_1-rmse:0.000614\n",
            "[938]\tvalidation_0-rmse:0.000613\tvalidation_1-rmse:0.000613\n",
            "[939]\tvalidation_0-rmse:0.000611\tvalidation_1-rmse:0.000611\n",
            "[940]\tvalidation_0-rmse:0.00061\tvalidation_1-rmse:0.00061\n",
            "[941]\tvalidation_0-rmse:0.000609\tvalidation_1-rmse:0.000609\n",
            "[942]\tvalidation_0-rmse:0.000607\tvalidation_1-rmse:0.000607\n",
            "[943]\tvalidation_0-rmse:0.000607\tvalidation_1-rmse:0.000607\n",
            "[944]\tvalidation_0-rmse:0.000606\tvalidation_1-rmse:0.000606\n",
            "[945]\tvalidation_0-rmse:0.000605\tvalidation_1-rmse:0.000605\n",
            "[946]\tvalidation_0-rmse:0.000604\tvalidation_1-rmse:0.000604\n",
            "[947]\tvalidation_0-rmse:0.000603\tvalidation_1-rmse:0.000603\n",
            "[948]\tvalidation_0-rmse:0.000602\tvalidation_1-rmse:0.000602\n",
            "[949]\tvalidation_0-rmse:0.000601\tvalidation_1-rmse:0.000601\n",
            "[950]\tvalidation_0-rmse:0.000601\tvalidation_1-rmse:0.000601\n",
            "[951]\tvalidation_0-rmse:0.0006\tvalidation_1-rmse:0.0006\n",
            "[952]\tvalidation_0-rmse:0.000599\tvalidation_1-rmse:0.000599\n",
            "[953]\tvalidation_0-rmse:0.000598\tvalidation_1-rmse:0.000598\n",
            "[954]\tvalidation_0-rmse:0.000598\tvalidation_1-rmse:0.000598\n",
            "[955]\tvalidation_0-rmse:0.000597\tvalidation_1-rmse:0.000597\n",
            "[956]\tvalidation_0-rmse:0.000596\tvalidation_1-rmse:0.000596\n",
            "[957]\tvalidation_0-rmse:0.000595\tvalidation_1-rmse:0.000595\n",
            "[958]\tvalidation_0-rmse:0.000595\tvalidation_1-rmse:0.000595\n",
            "[959]\tvalidation_0-rmse:0.000594\tvalidation_1-rmse:0.000594\n",
            "[960]\tvalidation_0-rmse:0.000593\tvalidation_1-rmse:0.000593\n",
            "[961]\tvalidation_0-rmse:0.000592\tvalidation_1-rmse:0.000592\n",
            "[962]\tvalidation_0-rmse:0.000591\tvalidation_1-rmse:0.000591\n",
            "[963]\tvalidation_0-rmse:0.000591\tvalidation_1-rmse:0.000591\n",
            "[964]\tvalidation_0-rmse:0.00059\tvalidation_1-rmse:0.00059\n",
            "[965]\tvalidation_0-rmse:0.000589\tvalidation_1-rmse:0.000589\n",
            "[966]\tvalidation_0-rmse:0.000588\tvalidation_1-rmse:0.000588\n",
            "[967]\tvalidation_0-rmse:0.000588\tvalidation_1-rmse:0.000588\n",
            "[968]\tvalidation_0-rmse:0.000587\tvalidation_1-rmse:0.000587\n",
            "[969]\tvalidation_0-rmse:0.000586\tvalidation_1-rmse:0.000586\n",
            "[970]\tvalidation_0-rmse:0.000585\tvalidation_1-rmse:0.000585\n",
            "[971]\tvalidation_0-rmse:0.000584\tvalidation_1-rmse:0.000584\n",
            "[972]\tvalidation_0-rmse:0.000584\tvalidation_1-rmse:0.000584\n",
            "[973]\tvalidation_0-rmse:0.000583\tvalidation_1-rmse:0.000583\n",
            "[974]\tvalidation_0-rmse:0.000582\tvalidation_1-rmse:0.000582\n",
            "[975]\tvalidation_0-rmse:0.000581\tvalidation_1-rmse:0.000581\n",
            "[976]\tvalidation_0-rmse:0.000581\tvalidation_1-rmse:0.000581\n",
            "[977]\tvalidation_0-rmse:0.00058\tvalidation_1-rmse:0.00058\n",
            "[978]\tvalidation_0-rmse:0.000579\tvalidation_1-rmse:0.000579\n",
            "[979]\tvalidation_0-rmse:0.000579\tvalidation_1-rmse:0.000579\n",
            "[980]\tvalidation_0-rmse:0.000578\tvalidation_1-rmse:0.000578\n",
            "[981]\tvalidation_0-rmse:0.000577\tvalidation_1-rmse:0.000577\n",
            "[982]\tvalidation_0-rmse:0.000576\tvalidation_1-rmse:0.000576\n",
            "[983]\tvalidation_0-rmse:0.000576\tvalidation_1-rmse:0.000576\n",
            "[984]\tvalidation_0-rmse:0.000575\tvalidation_1-rmse:0.000575\n",
            "[985]\tvalidation_0-rmse:0.000574\tvalidation_1-rmse:0.000574\n",
            "[986]\tvalidation_0-rmse:0.000574\tvalidation_1-rmse:0.000574\n",
            "[987]\tvalidation_0-rmse:0.000573\tvalidation_1-rmse:0.000573\n",
            "[988]\tvalidation_0-rmse:0.000573\tvalidation_1-rmse:0.000573\n",
            "[989]\tvalidation_0-rmse:0.000572\tvalidation_1-rmse:0.000572\n",
            "[990]\tvalidation_0-rmse:0.000571\tvalidation_1-rmse:0.000571\n",
            "[991]\tvalidation_0-rmse:0.000571\tvalidation_1-rmse:0.000571\n",
            "[992]\tvalidation_0-rmse:0.00057\tvalidation_1-rmse:0.00057\n",
            "[993]\tvalidation_0-rmse:0.000569\tvalidation_1-rmse:0.000569\n",
            "[994]\tvalidation_0-rmse:0.000569\tvalidation_1-rmse:0.000569\n",
            "[995]\tvalidation_0-rmse:0.000568\tvalidation_1-rmse:0.000568\n",
            "[996]\tvalidation_0-rmse:0.000567\tvalidation_1-rmse:0.000567\n",
            "[997]\tvalidation_0-rmse:0.000567\tvalidation_1-rmse:0.000567\n",
            "[998]\tvalidation_0-rmse:0.000566\tvalidation_1-rmse:0.000566\n",
            "[999]\tvalidation_0-rmse:0.000565\tvalidation_1-rmse:0.000565\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "XGBRegressor(learning_rate=0.0099, max_depth=15, n_estimators=1000)"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "predicted_results_v = xgb.predict(X_valid3)\n",
        "predicted_results_t = xgb.predict(X_train3)\n",
        "predicted_results_v= predicted_results_v.reshape(-1, 1)\n",
        "predicted_results_t= predicted_results_t.reshape(-1, 1)\n",
        "predicted_results_v = scaler1.inverse_transform(predicted_results_v)\n",
        "predicted_results_t = scaler.inverse_transform(predicted_results_t)"
      ],
      "metadata": {
        "id": "64oEKXVRRruo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "predicted_results_v = xgb.predict(X_valid3)\n",
        "predicted_results_t = xgb.predict(X_train3)\n",
        "predicted_results_v= predicted_results_v.reshape(-1, 1)\n",
        "predicted_results_t= predicted_results_t.reshape(-1, 1)\n",
        "predicted_results_v = scaler1.inverse_transform(predicted_results_v)\n",
        "predicted_results_t = scaler.inverse_transform(predicted_results_t)\n",
        "plt.figure(figsize=(20,15))\n",
        "plt.plot(X_train2.index,list(y_trainn),label=\"actual Price train\",color='b')\n",
        "plt.plot(X_train2.index,list(predicted_results_t),label=\"predicted Price train\",color='r')\n",
        "plt.plot(X_valid2.index,list(y_validn),label=\"actual Price valid\",color='m')\n",
        "plt.plot(X_valid2.index,list(predicted_results_v),label=\"predicted Price valid\",color='g')\n",
        "\n",
        "plt.xlabel('Date')\n",
        "plt.ylabel('Nifty 50 Closing Price')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 826
        },
        "id": "MSuImEZiRut8",
        "outputId": "e4d99833-8f79-4ded-df8d-2f78bc2d4c56"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x1080 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import plotly.graph_objects as go\n",
        "\n",
        "import pandas as pd\n",
        "from datetime import datetime\n",
        "\n",
        "df = pd.read_excel('data (2).xlsx')\n",
        "\n",
        "fig = go.Figure(data=[go.Candlestick(x=df['Date'],\n",
        "                open=df['Open'],\n",
        "                high=df['High'],\n",
        "                low=df['Low'],\n",
        "                close=df['Close'])])\n",
        "\n",
        "fig.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "UIbY1D7BDeqr",
        "outputId": "44d4cf60-348f-4e00-a0a1-6fefa1747a76"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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    {
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      "source": [
        "X_train"
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      "metadata": {
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          "height": 710
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        "id": "9kB9LZSQAA3_",
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              "                 Date      Open      High       Low  Shares Traded  Turnover  \\\n",
              "Date                                                                           \n",
              "2022-01-03 2022-01-03  17387.15  17646.65  17383.30      200456430  16181.36   \n",
              "2022-01-04 2022-01-04  17681.40  17827.60  17593.55      247437472  18604.16   \n",
              "2022-01-05 2022-01-05  17820.10  17944.70  17748.85      251460038  23737.31   \n",
              "2022-01-06 2022-01-06  17768.50  17797.95  17655.55      236454824  22643.82   \n",
              "2022-01-07 2022-01-07  17797.60  17905.00  17704.55      239338015  21447.89   \n",
              "...               ...       ...       ...       ...            ...       ...   \n",
              "2022-08-22 2022-08-22  17682.90  17690.05  17467.35      287559133  19605.44   \n",
              "2022-08-23 2022-08-23  17357.35  17625.55  17345.20      285616338  20365.80   \n",
              "2022-08-24 2022-08-24  17525.45  17623.65  17499.25      261953239  17819.88   \n",
              "2022-08-25 2022-08-25  17679.00  17726.50  17487.45      230181848  17566.70   \n",
              "2022-08-26 2022-08-26  17619.30  17685.85  17519.35      266636238  17500.80   \n",
              "\n",
              "            Open_mean_lag4  Open_std_lag7  High_mean_lag4  High_std_lag7  \\\n",
              "Date                                                                       \n",
              "2022-01-03    17210.912109     107.109695    17300.261719     104.598923   \n",
              "2022-01-04    17263.300781     134.337357    17399.363281     178.154724   \n",
              "2022-01-05    17378.625000     227.124100    17534.775391     251.821976   \n",
              "2022-01-06    17533.287109     258.395203    17704.937500     288.165009   \n",
              "2022-01-07    17664.287109     273.400879    17804.224609     277.789398   \n",
              "...                    ...            ...             ...            ...   \n",
              "2022-08-22    17882.636719     142.504395    17941.425781     161.694778   \n",
              "2022-08-23    17854.062500     117.831818    17904.162109     132.810730   \n",
              "2022-08-24    17726.363281     204.923950    17819.062500     150.844589   \n",
              "2022-08-25    17633.062500     220.189362    17732.863281     166.549332   \n",
              "2022-08-26    17561.175781     218.527283    17666.437500     169.248657   \n",
              "\n",
              "            Low_mean_lag4  Low_std_lag7  month  day  day_of_week  \n",
              "Date                                                              \n",
              "2022-01-03   17180.662109    152.019592      1    3            0  \n",
              "2022-01-04   17236.199219    189.507019      1    4            1  \n",
              "2022-01-05   17340.425781    233.424591      1    5            2  \n",
              "2022-01-06   17491.050781    237.741653      1    6            3  \n",
              "2022-01-07   17595.312500    245.675034      1    7            4  \n",
              "...                   ...           ...    ...  ...          ...  \n",
              "2022-08-22   17790.050781    144.736267      8   22            0  \n",
              "2022-08-23   17715.875000    137.871307      8   23            1  \n",
              "2022-08-24   17593.837891    191.512604      8   24            2  \n",
              "2022-08-25   17505.636719    199.691376      8   25            3  \n",
              "2022-08-26   17449.812500    198.150238      8   26            4  \n",
              "\n",
              "[162 rows x 15 columns]"
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              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Shares Traded</th>\n",
              "      <th>Turnover</th>\n",
              "      <th>Open_mean_lag4</th>\n",
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              "      <th>High_mean_lag4</th>\n",
              "      <th>High_std_lag7</th>\n",
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              "      <th>day_of_week</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2022-01-03</th>\n",
              "      <td>2022-01-03</td>\n",
              "      <td>17387.15</td>\n",
              "      <td>17646.65</td>\n",
              "      <td>17383.30</td>\n",
              "      <td>200456430</td>\n",
              "      <td>16181.36</td>\n",
              "      <td>17210.912109</td>\n",
              "      <td>107.109695</td>\n",
              "      <td>17300.261719</td>\n",
              "      <td>104.598923</td>\n",
              "      <td>17180.662109</td>\n",
              "      <td>152.019592</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>2022-01-04</th>\n",
              "      <td>2022-01-04</td>\n",
              "      <td>17681.40</td>\n",
              "      <td>17827.60</td>\n",
              "      <td>17593.55</td>\n",
              "      <td>247437472</td>\n",
              "      <td>18604.16</td>\n",
              "      <td>17263.300781</td>\n",
              "      <td>134.337357</td>\n",
              "      <td>17399.363281</td>\n",
              "      <td>178.154724</td>\n",
              "      <td>17236.199219</td>\n",
              "      <td>189.507019</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>2022-01-05</th>\n",
              "      <td>2022-01-05</td>\n",
              "      <td>17820.10</td>\n",
              "      <td>17944.70</td>\n",
              "      <td>17748.85</td>\n",
              "      <td>251460038</td>\n",
              "      <td>23737.31</td>\n",
              "      <td>17378.625000</td>\n",
              "      <td>227.124100</td>\n",
              "      <td>17534.775391</td>\n",
              "      <td>251.821976</td>\n",
              "      <td>17340.425781</td>\n",
              "      <td>233.424591</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-01-06</th>\n",
              "      <td>2022-01-06</td>\n",
              "      <td>17768.50</td>\n",
              "      <td>17797.95</td>\n",
              "      <td>17655.55</td>\n",
              "      <td>236454824</td>\n",
              "      <td>22643.82</td>\n",
              "      <td>17533.287109</td>\n",
              "      <td>258.395203</td>\n",
              "      <td>17704.937500</td>\n",
              "      <td>288.165009</td>\n",
              "      <td>17491.050781</td>\n",
              "      <td>237.741653</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>3</td>\n",
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              "    <tr>\n",
              "      <th>2022-01-07</th>\n",
              "      <td>2022-01-07</td>\n",
              "      <td>17797.60</td>\n",
              "      <td>17905.00</td>\n",
              "      <td>17704.55</td>\n",
              "      <td>239338015</td>\n",
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              "      <td>17664.287109</td>\n",
              "      <td>273.400879</td>\n",
              "      <td>17804.224609</td>\n",
              "      <td>277.789398</td>\n",
              "      <td>17595.312500</td>\n",
              "      <td>245.675034</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>4</td>\n",
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              "      <td>...</td>\n",
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              "      <th>2022-08-22</th>\n",
              "      <td>2022-08-22</td>\n",
              "      <td>17682.90</td>\n",
              "      <td>17690.05</td>\n",
              "      <td>17467.35</td>\n",
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              "      <td>19605.44</td>\n",
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              "      <td>142.504395</td>\n",
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              "      <td>161.694778</td>\n",
              "      <td>17790.050781</td>\n",
              "      <td>144.736267</td>\n",
              "      <td>8</td>\n",
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              "      <th>2022-08-23</th>\n",
              "      <td>2022-08-23</td>\n",
              "      <td>17357.35</td>\n",
              "      <td>17625.55</td>\n",
              "      <td>17345.20</td>\n",
              "      <td>285616338</td>\n",
              "      <td>20365.80</td>\n",
              "      <td>17854.062500</td>\n",
              "      <td>117.831818</td>\n",
              "      <td>17904.162109</td>\n",
              "      <td>132.810730</td>\n",
              "      <td>17715.875000</td>\n",
              "      <td>137.871307</td>\n",
              "      <td>8</td>\n",
              "      <td>23</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-08-24</th>\n",
              "      <td>2022-08-24</td>\n",
              "      <td>17525.45</td>\n",
              "      <td>17623.65</td>\n",
              "      <td>17499.25</td>\n",
              "      <td>261953239</td>\n",
              "      <td>17819.88</td>\n",
              "      <td>17726.363281</td>\n",
              "      <td>204.923950</td>\n",
              "      <td>17819.062500</td>\n",
              "      <td>150.844589</td>\n",
              "      <td>17593.837891</td>\n",
              "      <td>191.512604</td>\n",
              "      <td>8</td>\n",
              "      <td>24</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-08-25</th>\n",
              "      <td>2022-08-25</td>\n",
              "      <td>17679.00</td>\n",
              "      <td>17726.50</td>\n",
              "      <td>17487.45</td>\n",
              "      <td>230181848</td>\n",
              "      <td>17566.70</td>\n",
              "      <td>17633.062500</td>\n",
              "      <td>220.189362</td>\n",
              "      <td>17732.863281</td>\n",
              "      <td>166.549332</td>\n",
              "      <td>17505.636719</td>\n",
              "      <td>199.691376</td>\n",
              "      <td>8</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-08-26</th>\n",
              "      <td>2022-08-26</td>\n",
              "      <td>17619.30</td>\n",
              "      <td>17685.85</td>\n",
              "      <td>17519.35</td>\n",
              "      <td>266636238</td>\n",
              "      <td>17500.80</td>\n",
              "      <td>17561.175781</td>\n",
              "      <td>218.527283</td>\n",
              "      <td>17666.437500</td>\n",
              "      <td>169.248657</td>\n",
              "      <td>17449.812500</td>\n",
              "      <td>198.150238</td>\n",
              "      <td>8</td>\n",
              "      <td>26</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>162 rows × 15 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b4f15ef1-df05-40bb-b6cc-752f85eb21f9')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\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-convert: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-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",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-b4f15ef1-df05-40bb-b6cc-752f85eb21f9 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-b4f15ef1-df05-40bb-b6cc-752f85eb21f9');\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",
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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "xgb.predict([17373.00,17379.35,17184.95,219496063,18493.54,17425.500000,189.747696,17475.312500,133.749405,17294.800781,145.321899,12,16,3\n",
        "])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mc1JHnGvBzLY",
        "outputId": "e06b4564-41a7-46b0-fdfe-dde0eea41227"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.97359896], dtype=float32)"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_train"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x-Yv2Vo4CtHb",
        "outputId": "21b1274a-9155-4365-89da-c43ed6c663d0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Date\n",
              "2022-01-03    17625.70\n",
              "2022-01-04    17805.25\n",
              "2022-01-05    17925.25\n",
              "2022-01-06    17745.90\n",
              "2022-01-07    17812.70\n",
              "                ...   \n",
              "2022-08-22    17490.70\n",
              "2022-08-23    17577.50\n",
              "2022-08-24    17604.95\n",
              "2022-08-25    17522.45\n",
              "2022-08-26    17558.90\n",
              "Name: Close, Length: 162, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from numpy import asarray\n",
        "from pandas import read_csv\n",
        "row = [0.00632,18.00,2.310,0,0.5380,6.5750,65.20,4.0900,1,296.0,15.30,396.90,4.98,3]\n",
        "new_data = asarray([row])\n",
        "# make a prediction\n",
        "#using the model\n",
        "yhat = xgb.predict(new_data)\n",
        "print(yhat)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U8-milASptvG",
        "outputId": "aa913d5b-f2c3-4dfc-a62e-f026ffd8ac40"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0.9327907]\n"
          ]
        }
      ]
    }
  ]
}