Weather Preditction WIth Different Model.ipynb

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      "gpuType": "T4",
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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/trewto/Machine-Learning-Models/blob/main/Weather%20Preditction%20WIth%20Different%20Model.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#this may goood\n",
        "# Step 1: Import Libraries\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from sklearn.model_selection import train_test_split, GridSearchCV, cross_val_score\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from xgboost import XGBRegressor\n",
        "from sklearn.metrics import mean_squared_error, mean_absolute_error"
      ],
      "metadata": {
        "id": "j5ocO28qL5Lt"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Function of plotting graph**\n",
        "\n"
      ],
      "metadata": {
        "id": "GNOGu-ee1s1L"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "from sklearn.metrics import mean_squared_error, mean_absolute_error\n",
        "\n",
        "def evaluate_model(model, X_train_scaled, X_test_scaled, y_train, y_test, scaler_y):\n",
        "    \"\"\"\n",
        "    Evaluates the given model on training and testing data, and plots the results.\n",
        "\n",
        "    Parameters:\n",
        "    - model: Trained model to evaluate\n",
        "    - X_train_scaled: Scaled training features\n",
        "    - X_test_scaled: Scaled testing features\n",
        "    - y_train: Training target values\n",
        "    - y_test: Testing target values\n",
        "    - scaler_y: Scaler used to scale the target values\n",
        "    \"\"\"\n",
        "    # Predict\n",
        "    y_pred_train = model.predict(X_train_scaled)\n",
        "    y_pred_test = model.predict(X_test_scaled)\n",
        "\n",
        "    # Inverse transform the predictions\n",
        "    y_pred_train = scaler_y.inverse_transform(y_pred_train.reshape(-1, 1))\n",
        "    y_pred_test = scaler_y.inverse_transform(y_pred_test.reshape(-1, 1))\n",
        "\n",
        "    # Calculate metrics\n",
        "    mse_train = mean_squared_error(y_train, y_pred_train)\n",
        "    mse_test = mean_squared_error(y_test, y_pred_test)\n",
        "    mae_train = mean_absolute_error(y_train, y_pred_train)\n",
        "    mae_test = mean_absolute_error(y_test, y_pred_test)\n",
        "\n",
        "    # Print metrics\n",
        "    print(f'Training MSE: {mse_train:.2f}, Training MAE: {mae_train:.2f}')\n",
        "    print(f'Testing MSE: {mse_test:.2f}, Testing MAE: {mae_test:.2f}')\n",
        "\n",
        "    # Plot predictions vs actual values (Testing set)\n",
        "    plt.figure(figsize=(6, 3))\n",
        "    plt.plot(y_test.values, label='Actual')\n",
        "    plt.plot(y_pred_test, label='Predicted')\n",
        "    plt.legend()\n",
        "    plt.title('Actual vs Predicted Precipitation (Testing Set)')\n",
        "    plt.xlabel('Sample Index')\n",
        "    plt.ylabel('Precipitation')\n",
        "    plt.show()\n",
        "\n",
        "    # Plot predictions vs actual values (Training set)\n",
        "    plt.figure(figsize=(6, 3))\n",
        "    plt.plot(y_train.values, label='Actual')\n",
        "    plt.plot(y_pred_train, label='Predicted')\n",
        "    plt.legend()\n",
        "    plt.title('Actual vs Predicted Precipitation (Training Set)')\n",
        "    plt.xlabel('Sample Index')\n",
        "    plt.ylabel('Precipitation')\n",
        "    plt.show()\n"
      ],
      "metadata": {
        "id": "jVQ4vl7s1rva"
      },
      "execution_count": 63,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Reading database"
      ],
      "metadata": {
        "id": "3vB58_ct1vDo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#df = pd.read_csv('/content/drive/MyDrive/Colab Notebooks/2222.csv')\n",
        "df = pd.read_csv('/content/drive/MyDrive/Projects/Weather/data_set_2.csv')\n"
      ],
      "metadata": {
        "id": "1JHSfK9_L8xL"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.replace(-999, np.nan, inplace=True)"
      ],
      "metadata": {
        "id": "thXl6YgQNO0T"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.fillna(df.mean(), inplace=True)"
      ],
      "metadata": {
        "id": "8eAaMAmwNRs5"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print((df == -999).sum())\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GALUahxfNo0m",
        "outputId": "426898fe-55a7-4ed4-e286-418a8052f812"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "YEAR                   0\n",
            "MO                     0\n",
            "DY                     0\n",
            "HR                     0\n",
            "T2M                    0\n",
            "T2MDEW                 0\n",
            "T2MWET                 0\n",
            "QV2M                   0\n",
            "RH2M                   0\n",
            "PRECTOTCORR            0\n",
            "PS                     0\n",
            "WS2M                   0\n",
            "WD2M                   0\n",
            "WS10M                  0\n",
            "WD10M                  0\n",
            "ALLSKY_SFC_UV_INDEX    0\n",
            "dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
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          "height": 226
        },
        "id": "xXxpaE4HMhz6",
        "outputId": "a4ec4d24-34ef-4fdb-97da-2f881dccccbc"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "   YEAR  MO  DY  HR    T2M  T2MDEW  T2MWET  QV2M    RH2M  PRECTOTCORR      PS  \\\n",
              "0  2022   1   1   0  14.28   13.73   14.01  9.64   96.38          0.0  101.92   \n",
              "1  2022   1   1   1  13.83   13.71   13.77  9.64   99.06          0.0  101.91   \n",
              "2  2022   1   1   2  13.44   13.69   13.56  9.58  100.00          0.0  101.89   \n",
              "3  2022   1   1   3  13.21   13.65   13.44  9.58  100.00          0.0  101.87   \n",
              "4  2022   1   1   4  12.98   13.61   13.30  9.58  100.00          0.0  101.86   \n",
              "\n",
              "   WS2M    WD2M  WS10M   WD10M  ALLSKY_SFC_UV_INDEX  \n",
              "0  2.17  329.74   3.51  329.67                  0.0  \n",
              "1  2.26  331.75   3.57  331.75                  0.0  \n",
              "2  2.29  333.26   3.57  333.04                  0.0  \n",
              "3  2.23  333.79   3.46  333.72                  0.0  \n",
              "4  1.99  334.44   3.18  334.38                  0.0  "
            ],
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-2102d8e9-658a-426e-a0b4-70a4ad8356ee button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 22656,\n  \"fields\": [\n    {\n      \"column\": \"YEAR\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 2022,\n        \"max\": 2024,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          2022,\n          2023,\n          2024\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"MO\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3,\n        \"min\": 1,\n        \"max\": 12,\n        \"num_unique_values\": 12,\n        \"samples\": [\n          11,\n          10,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DY\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8,\n        \"min\": 1,\n        \"max\": 31,\n        \"num_unique_values\": 31,\n        \"samples\": [\n          28,\n          16,\n          24\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"HR\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 6,\n        \"min\": 0,\n        \"max\": 23,\n        \"num_unique_values\": 24,\n        \"samples\": [\n          8,\n          16,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"T2M\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5.691856324937805,\n        \"min\": 8.31,\n        \"max\": 42.7,\n        \"num_unique_values\": 2816,\n        \"samples\": [\n          14.69,\n          30.02,\n          33.05\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"T2MDEW\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5.720520530092944,\n        \"min\": 0.91,\n        \"max\": 28.45,\n        \"num_unique_values\": 2139,\n        \"samples\": [\n          14.94,\n          10.63,\n          26.97\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"T2MWET\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5.14457340104543,\n        \"min\": 8.08,\n        \"max\": 31.6,\n        \"num_unique_values\": 2126,\n        \"samples\": [\n          15.49,\n          13.34,\n          20.3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"QV2M\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5.200178822600595,\n        \"min\": 4.03,\n        \"max\": 24.54,\n        \"num_unique_values\": 325,\n        \"samples\": [\n          20.69,\n          13.12,\n          21.36\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"RH2M\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 18.78305813476348,\n        \"min\": 18.06,\n        \"max\": 100.0,\n        \"num_unique_values\": 1252,\n        \"samples\": [\n          35.0,\n          28.0,\n          66.12\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"PRECTOTCORR\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7810517858568939,\n        \"min\": 0.0,\n        \"max\": 23.65,\n        \"num_unique_values\": 458,\n        \"samples\": [\n          6.23,\n          0.15,\n          3.88\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"PS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.5694984619445964,\n        \"min\": 98.52,\n        \"max\": 102.13,\n        \"num_unique_values\": 315,\n        \"samples\": [\n          99.95,\n          101.53,\n          100.53\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WS2M\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.1770123557700654,\n        \"min\": 0.03,\n        \"max\": 13.12,\n        \"num_unique_values\": 664,\n        \"samples\": [\n          2.52,\n          3.69,\n          6.29\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WD2M\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 93.73227036928881,\n        \"min\": 0.0,\n        \"max\": 359.81,\n        \"num_unique_values\": 14408,\n        \"samples\": [\n          347.43,\n          205.22,\n          198.84\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WS10M\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.5648146040174584,\n        \"min\": 0.03,\n        \"max\": 18.37,\n        \"num_unique_values\": 896,\n        \"samples\": [\n          8.18,\n          6.05,\n          7.62\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"WD10M\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 93.69169957277839,\n        \"min\": 0.0,\n        \"max\": 359.86,\n        \"num_unique_values\": 14733,\n        \"samples\": [\n          110.47,\n          212.03,\n          231.33\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ALLSKY_SFC_UV_INDEX\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.419897878084771,\n        \"min\": 0.0,\n        \"max\": 14.58,\n        \"num_unique_values\": 499,\n        \"samples\": [\n          13.75,\n          2.92,\n          4.33\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#df.fillna(df.mean(), inplace=True)"
      ],
      "metadata": {
        "id": "ZQ6KGRUcMCKq"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Create lagged features\n",
        "def create_lagged_features(df, lag=5):\n",
        "  df_lagged = df.copy()\n",
        "  for i in range(1, lag + 1):\n",
        "      df_lagged[f'T2M_lag{i}'] = df_lagged['T2M'].shift(i)\n",
        "      df_lagged[f'T2MDEW_lag{i}'] = df_lagged['T2MDEW'].shift(i)\n",
        "      df_lagged[f'T2MWET_lag{i}'] = df_lagged['T2MWET'].shift(i)\n",
        "      df_lagged[f'RH2M_lag{i}'] = df_lagged['RH2M'].shift(i)\n",
        "      df_lagged[f'PS_lag{i}'] = df_lagged['PS'].shift(i)\n",
        "      df_lagged[f'WS2M_lag{i}'] = df_lagged['WS2M'].shift(i)\n",
        "      df_lagged[f'PRECTOTCORR_lag{i}'] = df_lagged['WD2M'].shift(i)\n",
        "  df_lagged.dropna(inplace=True)\n",
        "  return df_lagged"
      ],
      "metadata": {
        "id": "XoK_wMwPMH49"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "    # Apply the function\n",
        "l = 12\n",
        "df_lagged = create_lagged_features(df, lag=l-1)\n",
        "\n",
        "# Feature engineering\n",
        "df_lagged['T2M*QV2M'] = df_lagged['T2M'] * df_lagged['QV2M']\n",
        "df_lagged['T2M^2'] = df_lagged['T2M'] ** 2\n",
        "df_lagged['QV2M^2'] = df_lagged['QV2M'] ** 2\n",
        "\n",
        "lagged_features = [f'T2M_lag{i}' for i in range(1, l)] + \\\n",
        "                      [f'T2MDEW_lag{i}' for i in range(1, l)] + \\\n",
        "                      [f'T2MWET_lag{i}' for i in range(1, l)] + \\\n",
        "                      [f'RH2M_lag{i}' for i in range(1, l)] + \\\n",
        "                      [f'PS_lag{i}' for i in range(1, l)] + \\\n",
        "                      [f'WS2M_lag{i}' for i in range(1, l)]# + \\\n",
        "                     # [f'PRECTOTCORR_lag{i}' for i in range(1, l)]\n",
        "\n",
        "\n",
        "#features = ['MO', 'DY', 'HR', 'T2M', 'QV2M', 'PS', 'WS10M', 'T2M*QV2M', 'T2M^2', 'QV2M^2'] + lagged_features\n",
        "#features = ['T2M', 'QV2M', 'PS', 'WS10M', 'T2M*QV2M', 'T2M^2', 'QV2M^2'] + lagged_features\n",
        "features = ['HR','T2M*QV2M','T2M^2','QV2M^2','T2M', 'T2MDEW', 'T2MWET', 'QV2M', 'RH2M', 'PS', 'WS2M', 'WD2M', 'WS10M', 'WD10M'] +lagged_features\n",
        "#features = lagged_features\n",
        "\n",
        "target = 'PRECTOTCORR'\n",
        "\n",
        "X = df_lagged[features]\n",
        "\n",
        "y = df_lagged[target]"
      ],
      "metadata": {
        "id": "8mJo4kWEMKbp"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 255
        },
        "id": "Jm8loik4NEJV",
        "outputId": "5277e970-193f-422e-9294-c5b8334db9e3"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    HR  T2M*QV2M     T2M^2    QV2M^2    T2M  T2MDEW  T2MWET   QV2M   RH2M  \\\n",
              "11  11  204.4152  366.3396  114.0624  19.14   15.33   17.24  10.68  78.44   \n",
              "12  12  226.1844  443.5236  115.3476  21.06   15.36   18.21  10.74  69.75   \n",
              "13  13  240.3000  506.2500  114.0624  22.50   15.28   18.89  10.68  63.62   \n",
              "14  14  241.8240  524.4100  111.5136  22.90   15.08   18.99  10.56  61.31   \n",
              "15  15  241.9020  513.0225  114.0624  22.65   15.24   18.95  10.68  62.81   \n",
              "\n",
              "        PS  ...  WS2M_lag2  WS2M_lag3  WS2M_lag4  WS2M_lag5  WS2M_lag6  \\\n",
              "11  101.88  ...       2.14       2.30       2.05       1.62       1.78   \n",
              "12  101.78  ...       2.42       2.14       2.30       2.05       1.62   \n",
              "13  101.68  ...       2.59       2.42       2.14       2.30       2.05   \n",
              "14  101.62  ...       2.58       2.59       2.42       2.14       2.30   \n",
              "15  101.58  ...       2.14       2.58       2.59       2.42       2.14   \n",
              "\n",
              "    WS2M_lag7  WS2M_lag8  WS2M_lag9  WS2M_lag10  WS2M_lag11  \n",
              "11       1.99       2.23       2.29        2.26        2.17  \n",
              "12       1.78       1.99       2.23        2.29        2.26  \n",
              "13       1.62       1.78       1.99        2.23        2.29  \n",
              "14       2.05       1.62       1.78        1.99        2.23  \n",
              "15       2.30       2.05       1.62        1.78        1.99  \n",
              "\n",
              "[5 rows x 80 columns]"
            ],
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              "\n",
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              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>HR</th>\n",
              "      <th>T2M*QV2M</th>\n",
              "      <th>T2M^2</th>\n",
              "      <th>QV2M^2</th>\n",
              "      <th>T2M</th>\n",
              "      <th>T2MDEW</th>\n",
              "      <th>T2MWET</th>\n",
              "      <th>QV2M</th>\n",
              "      <th>RH2M</th>\n",
              "      <th>PS</th>\n",
              "      <th>...</th>\n",
              "      <th>WS2M_lag2</th>\n",
              "      <th>WS2M_lag3</th>\n",
              "      <th>WS2M_lag4</th>\n",
              "      <th>WS2M_lag5</th>\n",
              "      <th>WS2M_lag6</th>\n",
              "      <th>WS2M_lag7</th>\n",
              "      <th>WS2M_lag8</th>\n",
              "      <th>WS2M_lag9</th>\n",
              "      <th>WS2M_lag10</th>\n",
              "      <th>WS2M_lag11</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>11</td>\n",
              "      <td>204.4152</td>\n",
              "      <td>366.3396</td>\n",
              "      <td>114.0624</td>\n",
              "      <td>19.14</td>\n",
              "      <td>15.33</td>\n",
              "      <td>17.24</td>\n",
              "      <td>10.68</td>\n",
              "      <td>78.44</td>\n",
              "      <td>101.88</td>\n",
              "      <td>...</td>\n",
              "      <td>2.14</td>\n",
              "      <td>2.30</td>\n",
              "      <td>2.05</td>\n",
              "      <td>1.62</td>\n",
              "      <td>1.78</td>\n",
              "      <td>1.99</td>\n",
              "      <td>2.23</td>\n",
              "      <td>2.29</td>\n",
              "      <td>2.26</td>\n",
              "      <td>2.17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>12</td>\n",
              "      <td>226.1844</td>\n",
              "      <td>443.5236</td>\n",
              "      <td>115.3476</td>\n",
              "      <td>21.06</td>\n",
              "      <td>15.36</td>\n",
              "      <td>18.21</td>\n",
              "      <td>10.74</td>\n",
              "      <td>69.75</td>\n",
              "      <td>101.78</td>\n",
              "      <td>...</td>\n",
              "      <td>2.42</td>\n",
              "      <td>2.14</td>\n",
              "      <td>2.30</td>\n",
              "      <td>2.05</td>\n",
              "      <td>1.62</td>\n",
              "      <td>1.78</td>\n",
              "      <td>1.99</td>\n",
              "      <td>2.23</td>\n",
              "      <td>2.29</td>\n",
              "      <td>2.26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>13</td>\n",
              "      <td>240.3000</td>\n",
              "      <td>506.2500</td>\n",
              "      <td>114.0624</td>\n",
              "      <td>22.50</td>\n",
              "      <td>15.28</td>\n",
              "      <td>18.89</td>\n",
              "      <td>10.68</td>\n",
              "      <td>63.62</td>\n",
              "      <td>101.68</td>\n",
              "      <td>...</td>\n",
              "      <td>2.59</td>\n",
              "      <td>2.42</td>\n",
              "      <td>2.14</td>\n",
              "      <td>2.30</td>\n",
              "      <td>2.05</td>\n",
              "      <td>1.62</td>\n",
              "      <td>1.78</td>\n",
              "      <td>1.99</td>\n",
              "      <td>2.23</td>\n",
              "      <td>2.29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>14</td>\n",
              "      <td>241.8240</td>\n",
              "      <td>524.4100</td>\n",
              "      <td>111.5136</td>\n",
              "      <td>22.90</td>\n",
              "      <td>15.08</td>\n",
              "      <td>18.99</td>\n",
              "      <td>10.56</td>\n",
              "      <td>61.31</td>\n",
              "      <td>101.62</td>\n",
              "      <td>...</td>\n",
              "      <td>2.58</td>\n",
              "      <td>2.59</td>\n",
              "      <td>2.42</td>\n",
              "      <td>2.14</td>\n",
              "      <td>2.30</td>\n",
              "      <td>2.05</td>\n",
              "      <td>1.62</td>\n",
              "      <td>1.78</td>\n",
              "      <td>1.99</td>\n",
              "      <td>2.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>15</td>\n",
              "      <td>241.9020</td>\n",
              "      <td>513.0225</td>\n",
              "      <td>114.0624</td>\n",
              "      <td>22.65</td>\n",
              "      <td>15.24</td>\n",
              "      <td>18.95</td>\n",
              "      <td>10.68</td>\n",
              "      <td>62.81</td>\n",
              "      <td>101.58</td>\n",
              "      <td>...</td>\n",
              "      <td>2.14</td>\n",
              "      <td>2.58</td>\n",
              "      <td>2.59</td>\n",
              "      <td>2.42</td>\n",
              "      <td>2.14</td>\n",
              "      <td>2.30</td>\n",
              "      <td>2.05</td>\n",
              "      <td>1.62</td>\n",
              "      <td>1.78</td>\n",
              "      <td>1.99</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 80 columns</p>\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-3f1d52f9-2a36-4d34-a3cd-11f4b06f1969 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-3f1d52f9-2a36-4d34-a3cd-11f4b06f1969');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-7c01116b-b0fa-424e-b2d8-702ce60252ae\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-7c01116b-b0fa-424e-b2d8-702ce60252ae')\"\n",
              "            title=\"Suggest charts\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-7c01116b-b0fa-424e-b2d8-702ce60252ae button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "X"
            }
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "split_index = int(len(X) * 0.7)  # 70% for training and 30% for testing\n",
        "#or\n",
        "# Split the data sequentially\n",
        "#X_train = X[:split_index]\n",
        "#X_test = X[split_index:]\n",
        "#y_train = y[:split_index]\n",
        "#y_test = y[split_index:]\n",
        "\n",
        "#X =X[:split_index]\n",
        "#y = y[:split_index]\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.9, random_state=900)\n"
      ],
      "metadata": {
        "id": "kGSsLRzuMNMP"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "negative_values = y_train[y_train < 0]"
      ],
      "metadata": {
        "id": "cNO-bRasVNu1"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "# Step 6: Standardize the Data\n",
        "scaler = StandardScaler()\n",
        "X_train_scaled = scaler.fit_transform(X_train)\n",
        "X_test_scaled = scaler.transform(X_test)\n",
        "\n",
        "\n",
        "scaler_y = StandardScaler()\n",
        "y_train_scaled = scaler_y.fit_transform(y_train.values.reshape(-1, 1))\n",
        "y_test_scaled = scaler_y.transform(y_test.values.reshape(-1, 1))\n"
      ],
      "metadata": {
        "id": "2KZMkuWkMRvb"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "***Trial Error With Different type of MOdel***"
      ],
      "metadata": {
        "id": "dpAfkc2l128R"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**XGB**"
      ],
      "metadata": {
        "id": "hCLKqDZYSntk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "final_model = XGBRegressor(\n",
        "    colsample_bytree=0.3,\n",
        "    learning_rate=0.1,\n",
        "    max_depth=3,\n",
        "    n_estimators=300,\n",
        "    subsample=0.5,\n",
        "    random_state=45\n",
        ")\n",
        "final_model.fit(X_train_scaled,  y_train_scaled.ravel())\n"
      ],
      "metadata": {
        "id": "8runH_oRMU_d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "outputId": "527dac6e-e622-4bbc-91ae-73d6e1e0b03b"
      },
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "XGBRegressor(base_score=None, booster=None, callbacks=None,\n",
              "             colsample_bylevel=None, colsample_bynode=None,\n",
              "             colsample_bytree=0.3, device=None, early_stopping_rounds=None,\n",
              "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
              "             gamma=None, grow_policy=None, importance_type=None,\n",
              "             interaction_constraints=None, learning_rate=0.1, max_bin=None,\n",
              "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
              "             max_delta_step=None, max_depth=3, max_leaves=None,\n",
              "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
              "             multi_strategy=None, n_estimators=300, n_jobs=None,\n",
              "             num_parallel_tree=None, random_state=45, ...)"
            ],
            "text/html": [
              "<style>#sk-container-id-16 {color: black;}#sk-container-id-16 pre{padding: 0;}#sk-container-id-16 div.sk-toggleable {background-color: white;}#sk-container-id-16 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-16 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-16 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-16 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-16 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-16 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-16 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-16 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-16 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-16 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-16 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-16 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-16 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-16 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-16 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-16 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-16 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-16 div.sk-item {position: relative;z-index: 1;}#sk-container-id-16 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-16 div.sk-item::before, #sk-container-id-16 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-16 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-16 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-16 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-16 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-16 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-16 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-16 div.sk-label-container {text-align: center;}#sk-container-id-16 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-16 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-16\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>XGBRegressor(base_score=None, booster=None, callbacks=None,\n",
              "             colsample_bylevel=None, colsample_bynode=None,\n",
              "             colsample_bytree=0.3, device=None, early_stopping_rounds=None,\n",
              "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
              "             gamma=None, grow_policy=None, importance_type=None,\n",
              "             interaction_constraints=None, learning_rate=0.1, max_bin=None,\n",
              "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
              "             max_delta_step=None, max_depth=3, max_leaves=None,\n",
              "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
              "             multi_strategy=None, n_estimators=300, n_jobs=None,\n",
              "             num_parallel_tree=None, random_state=45, ...)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-19\" type=\"checkbox\" checked><label for=\"sk-estimator-id-19\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">XGBRegressor</label><div class=\"sk-toggleable__content\"><pre>XGBRegressor(base_score=None, booster=None, callbacks=None,\n",
              "             colsample_bylevel=None, colsample_bynode=None,\n",
              "             colsample_bytree=0.3, device=None, early_stopping_rounds=None,\n",
              "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
              "             gamma=None, grow_policy=None, importance_type=None,\n",
              "             interaction_constraints=None, learning_rate=0.1, max_bin=None,\n",
              "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
              "             max_delta_step=None, max_depth=3, max_leaves=None,\n",
              "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
              "             multi_strategy=None, n_estimators=300, n_jobs=None,\n",
              "             num_parallel_tree=None, random_state=45, ...)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "evaluate_model(final_model, X_train_scaled, X_test_scaled, y_train, y_test, scaler_y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 704
        },
        "id": "JxrgfeHA1-OZ",
        "outputId": "d979d8bd-d703-4470-a9cd-7d88562f1339"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training MSE: 0.04, Training MAE: 0.13\n",
            "Testing MSE: 0.34, Testing MAE: 0.26\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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PXC5XaXuqVq0KAAp1aHRx+fJlzJw5E1evXlW6gCQmJuqUxAF530W1atWU3qtevTouXbqkMM3KykrpMUPJkiWV6meow/LVhylIaGgoEhMTlepG5MqtuNmiRQv06NEDs2fPxvLly9GyZUt07doVP/zwA0QikU7rlJc/GQcUtzc2Nhbp6emoXLmy0nyqpqnTp08f9OnTB0lJSbh+/ToCAgKwc+dOdOrUCQ8fPoSVlRVCQ0Px5MkTtY95dKnEmvs9FOe+USgJKUbOnj2Ld+/eYffu3di9e7fS+zt27JAlIYWl7kchFovB4/Fkr7dv345Bgwaha9eumDx5MpydncHj8eDv7y+rZ6Gr77//HoMHD8bdu3dRr1497N27F61atVJ47t+8eXO8ePEChw4dwr///otNmzZh+fLlWL9+PYYNG1bgOurUqYPWrVsXOJ/8HS8gLe3hcDg4ceKEwn7IVaJECS220LiKOsbSpUvrvS8B4JdffoGfn5/Kz+hyASkqL168QKtWrVC9enUsW7YM7u7uEAqFOH78OJYvXy7bLmNS9b1qq1SpUlonK7kkEgmcnZ3VVoLPvSBzOBzs378f165dw5EjR3Dq1CkMGTIES5cuxbVr1/Q+9tRtr67JlLbs7e3Rpk0btGnTBgKBANu2bcP169fRokULSCQS1KlTB8uWLVP5WV3qUn38+BE2NjZKv43ihJKQYmTHjh1wdnbGmjVrlN4LDAzEwYMHsX79elhbW8PLywsPHz7UuDxN2XfJkiVVdtIUGRmpcFe5f/9+VKpUCYGBgQrLK0yT4a5du2LkyJGyRzLPnz9X2WzWyckJgwcPxuDBg5GSkoLmzZtj1qxZWiUh+vLy8gJjDBUrVpTdTavi4eEBQHoHKd/8Ljs7G+Hh4fD29lb72dz9q+/3VxQxGkLudgoEggKTGG2OZ3UkEglevnypsC+eP38OQNqCRR11+/fIkSPIzMzE4cOHFe7QVRXDa3uHm/tdPHv2TKm55rNnz2TvG0L16tUVSlK14eXlhTNnzqBp06ZaXTC//PJLfPnll5g/fz527tyJvn37Yvfu3Rg2bJhR7vqdnZ1hZWWFsLAwpfdUTdNFw4YNsW3bNrx79w6AdF/cu3cPrVq1KnBbCno/PDwcNWrUKFR85o7qhBQT6enpCAwMRMeOHdGzZ0+lv3HjxiE5OVnWtLFHjx64d++eyp4rc+8ecvu8UJVseHl54dq1a8jKypJNO3r0qFITz9w7FPk7kuvXr+Pq1at6b6ujoyP8/Pywd+9e7N69G0KhEF27dlWY5/379wqvS5QogcqVKxu9G+Tu3buDx+Nh9uzZSndhjDFZXA0bNkSZMmWwfv16hX0YEBBQYA+cZcqUQfPmzbFlyxZERUUprSOXuu+vKGI0BGdnZ7Rs2RIbNmyQneDlxcXFyf6vzfGsSW7T7tz5V69eDYFAgFatWqn9jLr9q+qYT0xMxNatW1UuQ5t92bBhQzg7O2P9+vUKx/CJEyfw5MkTdOjQocBlaKtx48Z4+PChTr+VXr16QSwWyx6RysvJyZFt48ePH5W+j9wWcrnrs7GxAaD6vKMvHo+H1q1bIygoCG/fvpVNDwsLw4kTJwr8fFpamtpzVu7ncx+V9erVC2/evMFff/2lNG96ejpSU1Nlrwv6/m/fvq1zi0RLQyUhxcThw4eRnJyMzp07q3z/yy+/RJkyZbBjxw707t0bkydPxv79+/Hdd99hyJAh8PHxwYcPH3D48GGsX78e3t7e8PLygqOjI9avXw87OzvY2trC19cXFStWxLBhw7B//360a9cOvXr1wosXL7B9+3alJmYdO3ZEYGAgunXrhg4dOiA8PBzr169HzZo1kZKSovf29u7dG/369cPatWvh5+enVMegZs2aaNmypayt/c2bN7F//36FCojG4OXlhXnz5mHatGmIiIhA165dYWdnh/DwcBw8eBAjRozAL7/8AoFAgHnz5mHkyJH45ptv0Lt3b4SHh2Pr1q1a1bdYuXIlvvrqKzRo0AAjRoxAxYoVERERgWPHjsm62ffx8QEA/Pbbb/j+++8hEAjQqVOnIovRENasWYOvvvoKderUwfDhw1GpUiXExMTg6tWreP36Ne7duwcAWh3P6lhZWeHkyZMYOHAgfH19ceLECRw7dgz/+9//NDbfVLd/27ZtC6FQiE6dOmHkyJFISUnBX3/9BWdnZ6VkysfHB+vWrcO8efNQuXJlODs7q+yYSiAQYNGiRRg8eDBatGiBPn36yJroenp64qefftJn96rUpUsXzJ07F+fPn9f68W2LFi0wcuRI+Pv74+7du2jbti0EAgFCQ0Oxb98+/Pnnn+jZsye2bduGtWvXolu3bvDy8kJycjL++usv2Nvb49tvvwUgfSxXs2ZN7NmzB1WrVoWTkxNq166tdx2oXLNmzcK///6Lpk2bYvTo0RCLxVi9ejVq165d4NAUaWlpaNKkCb788ku0a9cO7u7uSEhIQFBQEC5evIiuXbuifv36AID+/ftj7969GDVqFM6dO4emTZtCLBbj6dOn2Lt3L06dOiWr4O7j44MzZ85g2bJlcHNzQ8WKFWVDbdy6dQsfPnxAly5dCrXdZq+IW+MQI+nUqROzsrJiqampaucZNGgQEwgELD4+njHG2Pv379m4ceNYuXLlmFAoZOXLl2cDBw6Uvc8YY4cOHWI1a9aUNWOTb964dOlSVq5cOSYSiVjTpk3ZzZs3VXY5vmDBAubh4cFEIhGrX78+O3r0KBs4cCDz8PBQiA86dNuelJTErK2tGQC2fft2pffnzZvHGjVqxBwdHZm1tTWrXr06mz9/PsvKytK43Nymkfv27dM4X25TQfkmnPIOHDjAvvrqK2Zra8tsbW1Z9erV2dixY9mzZ88U5lu7di2rWLEiE4lErGHDhuzChQtK+1BV01LGGHv48CHr1q0bc3R0ZFZWVqxatWps+vTpCvPMnTuXlStXjnG5XKXmpIaMUR0PD48Cm0rnbt+SJUtUvv/ixQs2YMAA5urqygQCAStXrhzr2LEj279/v8J8BR3P6pro2trashcvXrC2bdsyGxsb5uLiwmbOnKnUZbqq41Pd/j18+DCrW7cus7KyYp6enmzRokVsy5YtSt9BdHQ069ChA7Ozs1No9py/iW6uPXv2sPr16zORSMScnJxY37592evXrxXmyd2m/FQ1b1Wnbt26bOjQoWrfz99EN9fGjRuZj48Ps7a2ZnZ2dqxOnTpsypQp7O3bt4wxxm7fvs369OnDKlSowEQiEXN2dmYdO3ZkN2/eVFjOlStXmI+PDxMKhQr7XV0T3bFjxyrFoqobgeDgYFa/fn0mFAqZl5cX27RpE/v555+ZlZWVxv2RnZ3N/vrrL9a1a1fZuczGxobVr1+fLVmyRKkbgqysLLZo0SJWq1YtJhKJWMmSJZmPjw+bPXs2S0xMlM339OlT1rx5c9m5TD7eqVOnsgoVKhT7bts5jBmp5g4hhJi5QYMGYf/+/YUqlSuO/vnnH4wdOxZRUVEqWzIVJ127di1Uc35jyMzMhKenJ3799VdMmDDB1OEYFdUJIYQQoqBv376oUKGCykruliw9PV3hdWhoKI4fP64w1IQ52Lp1KwQCgdqxlYoTKgkhhHy2qCTk81K2bFkMGjQIlSpVQmRkJNatW4fMzEzcuXNHbb85xLioYiohhJDPQrt27bBr1y5ER0dDJBKhcePGWLBgASUgJkQlIYQQQggxCaoTQgghhBCToCSEEEIIISZBdUJUkEgkePv2Lezs7Ir1wEGEEEKIoTHGkJycDDc3N3C5mss6KAlR4e3btzoNMkQIIYQQRa9evUL58uU1zkNJiAp2dnYApDvQ3t7exNEQQgghliMpKQnu7u6ya6kmlISokPsIxt7enpIQQgghRA/aVGegiqmEEEIIMQlKQgghhBBiEpSEEEIIIcQkqE4IIcUQYww5OTkQi8WmDoXogcfjgc/nUxcBpNijJISQYiYrKwvv3r1DWlqaqUMhhWBjY4OyZctCKBSaOhRCjIaSEEKKEYlEgvDwcPB4PLi5uUEoFNLdtIVhjCErKwtxcXEIDw9HlSpVCuzwiRBLRUkIIcVIVlYWJBIJ3N3dYWNjY+pwiJ6sra0hEAgQGRmJrKwsWFlZmTokYqGWn36O2ORMLOhW2yxvSEyaXl+4cAGdOnWCm5sbOBwOgoKCFN4fNGgQOByOwl+7du0KXO6aNWvg6ekJKysr+Pr64saNG0baAkLME905Wz76Dokh/Bkcil03ovA8JsXUoahk0qM8NTUV3t7eWLNmjdp52rVrh3fv3sn+du3apXGZe/bswaRJkzBz5kzcvn0b3t7e8PPzQ2xsrKHDJ4QQQixCVo7E1CGoZNLHMe3bt0f79u01ziMSieDq6qr1MpctW4bhw4dj8ODBAID169fj2LFj2LJlC3799ddCxUsIIYQQwzH78r6QkBA4OzujWrVqGD16NN6/f6923qysLNy6dQutW7eWTeNyuWjdujWuXr2q9nOZmZlISkpS+COEEAAqHxUTQgzDrJOQdu3a4e+//0ZwcDAWLVqE8+fPo3379mr7PoiPj4dYLIaLi4vCdBcXF0RHR6tdj7+/PxwcHGR/NIIuIaZx9epV8Hg8dOjQQafPeXp6YsWKFcYJihBiNGadhHz//ffo3Lkz6tSpg65du+Lo0aP477//EBISYtD1TJs2DYmJibK/V69eGXT5hBDtbN68GT/++CMuXLiAt2/fmjocQoiRmXUSkl+lSpVQunRphIWFqXy/dOnS4PF4iImJUZgeExOjsV6JSCSSjZhLI+eS4oQxhrSsHJP8McZ0ijUlJQV79uzB6NGj0aFDBwQEBCi8f+TIEXzxxRewsrJC6dKl0a1bNwBAy5YtERkZiZ9++knWig4AZs2ahXr16iksY8WKFfD09JS9/u+//9CmTRuULl0aDg4OaNGiBW7fvq3zfiaE6Mei+gl5/fo13r9/j7Jly6p8XygUwsfHB8HBwejatSsAaedNwcHBGDduXBFGSoh5SM8Wo+aMUyZZ9+M5frARan+K2bt3L6pXr45q1aqhX79+mDhxIqZNmwYOh4Njx46hW7du+O233/D3338jKysLx48fBwAEBgbC29sbI0aMwPDhw3WKMTk5GQMHDsSqVavAGMPSpUvx7bffIjQ0FHZ2djotixCiO5MmISkpKQqlGuHh4bh79y6cnJzg5OSE2bNno0ePHnB1dcWLFy8wZcoUVK5cGX5+frLPtGrVCt26dZMlGZMmTcLAgQPRsGFDNGrUCCtWrEBqaqqstQwhxDxt3rwZ/fr1AyCtD5aYmIjz58+jZcuWmD9/Pr7//nvMnj1bNr+3tzcAwMnJCTweD3Z2dlq3pMvOkeBDWhaatWgJAS+vQHjjxo1wdHTE+fPn0bFjRwNuHSFEFZMmITdv3sTXX38tez1p0iQAwMCBA7Fu3Trcv38f27ZtQ0JCAtzc3NC2bVvMnTsXIpFI9pkXL14gPj5e9rp3796Ii4vDjBkzEB0djXr16uHkyZNKlVUJ+RxYC3h4PMev4BmNtG5tPXv2DDdu3MDBgwcBAHw+H71798bmzZvRsmVL3L17V+dSDk3C36ciI1uM8Ki32PynP0JCQhAbGwuxWIy0tDRERUUZbF2EEPVMmoS0bNlS43PjU6cKLkaOiIhQmjZu3Dh6/EIIpM1LdXkkYiqbN29GTk4O3NzcZNMYYxCJRFi9ejWsra11XiaXy1U6v2RnZwMAMrKlLex+HjcCWamJ+PPPP+Hh4QGRSITGjRsjKyurEFtDiPlh0K2OVlGxqIqphJDiJycnB3///TeWLl2Ku3fvyv7u3bsHNzc37Nq1C3Xr1kVwcLDaZQiFQqWm+2XKlEF0dLRCInL37l2Fee7evI7x48fj22+/Ra1atSASiRRKVgkhxmX+t0iEkGLt6NGj+PjxI4YOHQoHBweF93r06IHNmzdjyZIlaNWqFby8vPD9998jJycHx48fx9SpUwFI+wm5cOECvv/+e4hEIpQuXRotW7ZEXFwcFi9ejJ49e+LkyZM4ceKEQuu3ChUr4Z9//kHDhg2RlJSEyZMn61XqQgjRD5WEEEJMavPmzWjdurVSAgJIk5CbN2/CyckJ+/btw+HDh1GvXj188803CgNTzpkzBxEREfDy8kKZMmUAADVq1MDatWuxZs0aeHt748aNG/jll18Ulj9rySp8/PgRDRo0QP/+/TF+/Hg4Ozsbd4MJITIcpmtj/s9AUlISHBwckJiYSH2GEIuSkZGB8PBwVKxYkYZ/1+D+6wTZ/+uWdzRZHJrQd0kMwfPXYwCAw+OaFtmxrss1lEpCCCGEEGISlIQQQgghxCQoCSGEEEKISVASQgghhBCToCSEEEIIISZBSQghhBBSzJlrO1hKQgghhBBiEpSEEEIIIcQkKAkhhBBCiElQEkII+awMGjQIE4f2lb1u2bIlJk6cWORxhISEgMPhICEhocjXTYi5oCSEEGIWBg0aBA6HAw6HA6FQiMqVK2POnDnIyckx6noDAwMxd+5crealxIEQw6JRdAkhZqNdu3bYunUrMjMzcfz4cYwdOxYCgQDTpk1TmC8rKwtCodAg63RycjLIcgghuqOSEEKKM8aArFTT/OnRJlAkEsHV1RUeHh4YPXo0WrdujcOHD2PQoEHo2rUr5s+fDzc3N1SrVg0A8OrVK/Tq1QuOjo5wcnJCly5dEBERIVueWCzGpEmT4OjoiFKlSmHKlCnIP2Zn/scxmZmZmDp1Ktzd3SESiVC5cmVs3rwZERER+PrrrwEAJUuWBIfDwaBBgwAAEokE/v7+qFixIqytreHt7Y39+/crrOf48eOoWrUqrK2t8fXXXyvEScjnikpCCCnOstOABW6mWff/3gJC20ItwtraGu/fvwcABAcHw97eHqdPnwYAZGdnw8/PD40bN8bFixfB5/Mxb948tGvXDvfv34dQKMTSpUsREBCALVu2oEaNGli6dCkOHjyIho2bqV3ngAEDcPXqVaxcuRLe3t4IDw9HfHw83N3dceDAAfTo0QPPnj2Dvb09rK2tAQD+/v7Yvn071q9fjypVquDChQvo168fypQpgxYtWuDVq1fo3r07xo4dixEjRuDmzZv4+eefC7VvCCkOKAkhhJgdxhiCg4Nx6tQp/Pjjj4iLi4OtrS02bdokewyzfft2SCQSbNq0CRwOBwCwdetWODo6IiQkBG3btsWKFSswbdo0dO/eHQCwfv16nDp1Su16nz9/jr179+L06dNo3bo1AKBSpUqy93Mf3Tg7O8PR0RGAtORkwYIFOHPmDBo3biz7zKVLl7Bhwwa0aNEC69atg5eXF5YuXQoAqFatGh48eIBFixYZcK8RYnkoCSGkOBPYSEskTLVuHR09ehQlSpRAdnY2JBIJfvjhB8yaNQtjx45FnTp1FOqB3Lt3D2FhYbCzs1NYRkZGBl68eIHExES8e/cOvr6+svf4fD4aNmyIxLQsleu/e/cueDweWrRooXXMYWFhSEtLQ5s2bRSmZ2VloX79+gCAJ0+eKMQBQJawEFIUzLTDVEpCiov7rxMwevttTPu2OjrWNVHxOzE/HE6hH4kUpa+//hrr1q2DUCiEm5sb+Py8U5StreJ2pKSkwMfHBzt27FBaTpkyZfRaf+7jFV2kpKQAAI4dO4Zy5copvCcSifSKg5DPBSUhxcSof27hbWIGxu28Q0kIsVi2traoXLmyVvM2aNAAe/bsgbOzM+zt7VXOU7ZsWVy/fh3NmzcHAOTk5ODWrVuoXKOOyvnr1KkDiUSC8+fPyx7HyMstiRGLxbJpNWvWhEgkQlRUlNoSlBo1auDw4cMK065du1bwRhJSzFHrmGIiSywxdQiEFKm+ffuidOnS6NKlCy5evIjw8HCEhIRg/PjxeP36NQBgwoQJWLhwIYKCgvD06VOMGTNGYx8fnp6eGDhwIIYMGYKgoCDZMvfu3QsA8PDwAIfDwdGjRxEXF4eUlBTY2dnhl19+wU8//YRt27bhxYsXuH37NlatWoVt27YBAEaNGoXQ0FBMnjwZz549w86dOxEQEGDsXUSI2TNpEnLhwgV06tQJbm5u4HA4CAoKkr2XnZ2NqVOnok6dOrC1tYWbmxsGDBiAt281P9+eNWuWrMOj3L/q1asbeUuK1tPoJLyMSzF1GISYlI2NDS5cuIAKFSqge/fuqFGjBoYOHYqMjAxZycjPP/+M/v37Y+DAgWjcuDHs7OzQrVs3jctdt24devbsiTFjxqB69eoYPnw4UlNTAQDlypXD7Nmz8euvv8LFxQXjxo0DAMydOxfTp0+Hv78/atSogXbt2uHYsWOoWLEiAKBChQo4cOAAgoKC4O3tjfXr12PBggVG3DuEWAYOy99ovgidOHECly9fho+PD7p3746DBw+ia9euAIDExET07NkTw4cPh7e3Nz5+/IgJEyZALBbj5s2bapc5a9Ys7N+/H2fOnJFN4/P5KF26tNZxJSUlwcHBAYmJiWqLeU0lMT0b3rP/BQCE+38raxXQcN5pxKdIK9tFLOxgsviIaWVkZCA8PBwVK1aElZWVqcMxW/dfJ8j+X7e8o8ni0IS+S2IInr8eAwAcGtsU3u6ORbJOXa6hJq0T0r59e7Rv317lew4ODrL+AHKtXr0ajRo1QlRUFCpUqKB2uXw+H66urgaN1VzEJWeYOgRCCCHEICyqTkhiYiI4HI6sfb46oaGhcHNzQ6VKldC3b19ERUVpnD8zMxNJSUkKf4QQQggxLotJQjIyMjB16lT06dNHY/GOr68vAgICcPLkSaxbtw7h4eFo1qwZkpOT1X7G398fDg4Osj93d3djbAIhhBBC5FhEEpKdnY1evXqBMYZ169ZpnLd9+/b47rvvULduXfj5+eH48eNISEiQ1W5XZdq0aUhMTJT9vXr1ytCbQAghhJgUYwxnn8YgOtF8HuubfT8huQlIZGQkzp49q3NFUUdHR1StWhVhYWFq5xGJRNSpEClWTFjfnBiItt9hfEom3nxML7JKh8RyHX8QjbE7bwMwnwYMZl0SkpuAhIaG4syZMyhVqpTOy0hJScGLFy9QtmxZI0RoTjimDoCYAYFAAABIS0szcSSksHK/w9zvVJ2G886gy5rLuBX5sSjCIhaKAbgUFm/qMJSYtCQkJSVFoYQiPDwcd+/ehZOTE8qWLYuePXvi9u3bOHr0KMRiMaKjowFIB5HK7bmwVatW6Natm6y9/i+//IJOnTrBw8MDb9++xcyZM8Hj8dCnT5+i30BCihiPx4OjoyNiY2MBSPvSyG3GTfKwnLyxYzIyzKdoGpCWgKSlpSE2NhaOjo7g8Xhafe7qi3j4eJQ0cnSEGJZJk5CbN2/i66+/lr2eNGkSAGDgwIGYNWuWrJvjevXqKXzu3LlzaNmyJQDgxYsXiI/Py+5ev36NPn364P379yhTpgy++uorXLt2Te+xJAixNLnN03MTEZJHwhjSMsVISM+WTROm6z5eTFFwdHQstl0NEJLLpElIy5YtNT731OaZaEREhMLr3bt3FzYsQiwah8NB2bJl4ezsjOzs7II/8BlZceY5jtxT7HU5+OeWpglGA4FAoHUJCCGWzOwrphJC9MPj8ehCls/JJ+/xJlmsMI16IyXEdMy6YiohhBBCii9KQgghRWbZ6edYcPyJqcMghJgJehxDCCkSmTlirAwOBQAMaVoRrg70GISQzx2VhBBC9HI5LB5/nHoGsUS7TrXk65lniyVGiurzRf3TkYKYY2t9KgkpJszx4CLFW99N1wEA5Uta4/tG6ke1JoQQdagkhBBSKK8+Uu+shJi7/F1edFlzGZsvhZsomjyUhBBCCCGfmXuvEjD36GNTh0FJCCHk80Fd2BNiXigJIYQQQohJUBJCCCGEEJOgJKSYoOZ5xJLQ8UoIASgJIYQQQj4L5lgjipIQC6PuDpLq2xHyeaPCJWKJKAmxYFSkTQghxJJREkIIIYQQk6AkhBDy2aCnluRzZa4F55SEEEIIIcQkKAkhhBQ5Zrb3ZYSQokRJiIWhVjDEUtGxS4hpmWPqT0kIIYQQQkxCryQkJiYG/fv3h5ubG/h8Png8nsIfIYQQQsyLORZG6pWEDBo0CLdv38b06dOxf/9+BAYGKvxp68KFC+jUqRPc3NzA4XAQFBSk8D5jDDNmzEDZsmVhbW2N1q1bIzQ0tMDlrlmzBp6enrCysoKvry9u3Lih6yZaHE0Hl1hijoVwhBBCPnd8fT506dIlXLx4EfXq1SvUylNTU+Ht7Y0hQ4age/fuSu8vXrwYK1euxLZt21CxYkVMnz4dfn5+ePz4MaysrFQuc8+ePZg0aRLWr18PX19frFixAn5+fnj27BmcnZ0LFa8lmnPkMfbdeoXTP7WAq4PqfUYIIYSYgl4lIe7u7mAG6K6zffv2mDdvHrp166b0HmMMK1aswO+//44uXbqgbt26+Pvvv/H27VulEhN5y5Ytw/DhwzF48GDUrFkT69evh42NDbZs2VLoeC3RlsvhSM7IwcYLL00dCiGmZ47l0YQUAXM99PVKQlasWIFff/0VERERBg4nT3h4OKKjo9G6dWvZNAcHB/j6+uLq1asqP5OVlYVbt24pfIbL5aJ169ZqPwMAmZmZSEpKUvgjhBgWDTNACMlPr8cxvXv3RlpaGry8vGBjYwOBQKDw/ocPHwodWHR0NADAxcVFYbqLi4vsvfzi4+MhFotVfubp06dq1+Xv74/Zs2cXMmJCiLZMlpBQIkQ+U+Z66OuVhKxYscLAYZjWtGnTMGnSJNnrpKQkuLu7mzAiYlAxj4CsVMC9kakj+axRPyGEkPz0SkIGDhxo6DiUuLq6ApA2By5btqxsekxMjNoKsaVLlwaPx0NMTIzC9JiYGNnyVBGJRBCJRIUPmpindU2k//4SCpT4/ConGxvHbJ82E0LMnd6dlYnFYhw4cADz5s3DvHnzcPDgQYjFYoMFVrFiRbi6uiI4OFg2LSkpCdevX0fjxo1VfkYoFMLHx0fhMxKJBMHBwWo/Qz4jSW9MHQEhRqPNI67oxAxkZBvuPE0sizmWRupVEhIWFoZvv/0Wb968QbVq1QBI61W4u7vj2LFj8PLy0mo5KSkpCAsLk70ODw/H3bt34eTkhAoVKmDixImYN28eqlSpImui6+bmhq5du8o+06pVK3Tr1g3jxo0DAEyaNAkDBw5Ew4YN0ahRI6xYsQKpqakYPHiwPptqMczx4CJEHTpei15oTDLaLL+A8iWtcWnqN6YOhxAAeiYh48ePh5eXF65duwYnJycAwPv379GvXz+MHz8ex44d02o5N2/exNdffy17nVsvY+DAgQgICMCUKVOQmpqKESNGICEhAV999RVOnjyp0EfIixcvEB8fL3vdu3dvxMXFYcaMGYiOjka9evVw8uRJpcqqhBDDoMHoLMOpR9IK/a8/pps4EkLy6JWEnD9/XiEBAYBSpUph4cKFaNq0qdbLadmypcb+RjgcDubMmYM5c+aonUdVM+Fx48bJSkYIIUSGSmAIMSt61QkRiURITk5Wmp6SkgKhUFjooAghhBBS/OmVhHTs2BEjRozA9evXwRgDYwzXrl3DqFGj0LlzZ0PHSAgpZqjjMssVk5SB4CcxkNCYVMQA9EpCVq5cCS8vLzRu3BhWVlawsrJC06ZNUblyZfz555+GjpEQUgxQU97iodmicxi67SaC7lJrM1J4etUJcXR0xKFDhxAaGirribRGjRqoXLmyQYMjytTdQRbHO8tDd9/g2P13WN67HmxFeh2q+dBFkJDCyhJLAAAXQ+PRvUF5E0dDLF2hzuxVqlRBlSpVDBULIQom7L4LANhw4SUmtalq2mAIMXPUSolowph5lkZqnYRMmjQJc+fOha2trUIX56osW7as0IERkisxLctAS6KTNCGEmBOtk5A7d+4gOztb9n9ievKXVOr8iRBCiKXROgk5d+6cyv8Tw0nLyoGN0BB1HwghqlCuToh50at1zJAhQ1T2E5KamoohQ4YUOqjP0bH771BzximsC3lh6lAIIYSQIqFXErJt2zakpyt3/Zueno6///670EF9jn7edxcAsOjkU9MGUqzRfbC5oNo5hBQ9c6y8rFPZf1JSkqxzsuTkZIUxXMRiMY4fPw5nZxoq3RyZ48FHCCHk86ZTEuLo6AgOhwMOh4OqVZWbTHI4HMyePdtgwRFCCNGOOTa/JKQgOiUh586dA2MM33zzDQ4cOKAwgJ1QKISHhwfc3NwMHiQhhBDNqLSTFMQcE1WdkpAWLVoAAMLDw+Hu7g4uV68qJcQEzPHgI4QUneLYqzKxfHq1B/Xw8AAApKWlISoqCllZip1J1a1bt/CRfWYKe4KgJIMQQoh65pmF6pWExMXFYfDgwThx4oTK98VicaGCIupRp2TEUpnD4wIO/YAIMSt6PU+ZOHEiEhIScP36dVhbW+PkyZPYtm0bqlSpgsOHDxs6RmJBUjJz4Lf8AhZTU+PPBpXCEUL0pVdJyNmzZ3Ho0CE0bNgQXC4XHh4eaNOmDezt7eHv748OHToYOk5iIXZdj8KzmGQ8i0nGlHbVTR0OMVOMKigUOSoEIuZIr5KQ1NRUWX8gJUuWRFxcHACgTp06uH37tuGiIxYnR0IXF0LIJ2kfgE2tgf82mzoSYqb0SkKqVauGZ8+eAQC8vb2xYcMGvHnzBuvXr0fZsmUNGiAhhBALdWEJ8Po/4JjmkdfJ50uvxzETJkzAu3fvAAAzZ85Eu3btsGPHDgiFQgQEBBgyvs8GlR8QYnzF+TFQUW+aVvsyK8X4gRCtmeMjOb2SkH79+sn+7+Pjg8jISDx9+hQVKlRA6dKlDRYcIYQQ81KLE4Fm3PuIY0NNHQopBvR6HDNnzhykpaXJXtvY2KBBgwawtbXFnDlzDBYcsTzmmGnLmHVwhOhnKn8XzgonQZSjPLK5MRwT/Q+/Cnaj+cfAIlkfKd70SkJmz56NlBTlYra0tDSDjx3j6ekpG69G/m/s2LEq5w8ICFCaV36gveKKrq/EVPTp/8NU/XUUx35CRvOPoBI3GnWj9xfpestlhBXp+kjxpNfjGMaYyh/zvXv3FMaTMYT//vtPofOzhw8fok2bNvjuu+/Ufsbe3l5WcRYoniceQgiRxynG9V1I8aVTElKyZEmFUXTlL+5isRgpKSkYNWqUQQMsU6aMwuuFCxfCy8tLNo6NKhwOB66urgaNw+jo/GF8dJI2G8W5gighRHs6JSErVqwAYwxDhgzB7Nmz4eDgIHtPKBTC09MTjRs3NniQubKysrB9+3ZMmjRJY+lGSkoKPDw8IJFI0KBBAyxYsAC1atVSO39mZiYyMzNlr5OSkgwatza0LdI293M3lTkRQgjRlk5JyMCBAwEAFStWRJMmTSAQCIwSlDpBQUFISEjAoEGD1M5TrVo1bNmyBXXr1kViYiL++OMPNGnSBI8ePUL58uVVfsbf39/gdVkIIYQQopnWFVPlSwfq16+P9PR0JCUlqfwzls2bN6N9+/Zwc3NTO0/jxo0xYMAA1KtXDy1atEBgYCDKlCmDDRs2qP3MtGnTkJiYKPt79eqVMcI3KnMvITEZ2jHks0HHOrE8WpeElCxZEu/evYOzszMcHR1VPg7JrbBqjFF0IyMjcebMGQQG6tYsTCAQoH79+ggLU1+TWyQSQSQSFTZEs2YOI5iaHFVQJp8xyseJOZ4BtU5Czp49K2v5cu7cOaMFpM7WrVvh7Oys8+B4YrEYDx48wLfffmukyExHWrnPHA8rQgghRhFxCeAKgAq+po7EILROQuRbo2hqmWIMEokEW7duxcCBA8HnK4Y8YMAAlCtXDv7+/gCkHal9+eWXqFy5MhISErBkyRJERkZi2LBhRRpzUTOXm3xziYMQVejwJBYtPQEI+HQjPj0e4BVtvUxj0KufEAD4+PEjNm/ejCdPngAAatasicGDBxu8nxAAOHPmDKKiojBkyBCl96KiosDl5lVt+fjxI4YPH47o6GiULFkSPj4+uHLlCmrWrGnwuAyJikrJ54QOd0L0kJGQ939JzuebhFy4cAGdOnWCg4MDGjZsCABYuXIl5syZgyNHjqB58+YGDbJt27Zq+xUICQlReL18+XIsX77coOsnxJKkZ4lx+kkMWlQtAwdryz9JEW1Rakc0M8cjRK8kZOzYsejduzfWrVsHHo8HQFr3YsyYMRg7diwePHhg0CAJIdqbfugh9t96jUaeTtg7ynj99hDzYpaPmqiI12yY61eh19gxYWFh+Pnnn2UJCADweDxMmjRJYysUYjoc8zxFGZ+5/vKMKPD2awDAjYgPJo6EGMqbhHSsOReGxLRsvZdB9bWIOdIrCWnQoIGsLoi8J0+ewNvbu9BBEanMHDHeJqSbOgxCiIn1WHsFS049w5QD90wdSrGTmJaNhLQsU4ehu2Jyg6XX45jx48djwoQJCAsLw5dffgkAuHbtGtasWYOFCxfi/v37snnr1q1rmEiLKYmE4dHbJORIlA+oTqsu4XlMCo6M+wp1yjuo+DQhlqOYnDNNIjopAwBwJey92nnMcfcmZeTA3tRBaJAjlsB7zr8AgOfz2kPI1/6+XN1ArsZVuPWZY2GYXklInz59AABTpkxR+R6HwzFqx2XFydLTz7Dm3AuV7z2PSQEAHLn/lpIQYnZKIgkVOLHgoLKpQyEmUXDa8zQ6GY2KIBJ9JWfkyP6fmJ6NMnbadVoZFpuMXhuuYUxLLwxrVslY4RWJ1Mwc2Ir0bihbaHqtOTw83NBxfLbUJSCEmLsborEQcMTYneQMoJqpw9EK1YsghjA96BE+pGZh3rEnFp+ELDn1DLM6qx/g1dj0SkI8PDwMHQcpgFjF4xp55nJu/WwrwH6GBBxpKadnwjUAfXT6LD2aKQ7M77f+Mi4FEgZUdi5h1PUUp2EwHr8r+lHj5WmdhBw+fBjt27eHQCDA4cOHNc7buXPnQgdG8kgkDG2WnYeYMWzs39DU4ViY4nOyIISOZvWyxRJ8s/Q8AODxHD/YCE33iKFoFI+jQetvqWvXroiOjoazszO6du2qdj6qB2J4ienZeBmfCgB4n5pp4mgsmfnduRkDh8Ohogby2UnPzrvuJKRl65yEWETpRjF8nqj1tySRSFT+n+hGLGF4HpOM6q52etWspscd+ktMzwZV7yXFFcccE08zP10Vw2u67kx82OjVTwjR39QD99H+z4tYfVb7Tt3M5dQy7+hjjN15W20X+oB5/6hjk6kUiRBCzIleScj48eOxcuVKpemrV6/GxIkTCxtTsbb/lrQ3y1U6JCHmYtOlcBy7/87kFZn0Zo53ioQUETr8i4FCfIkMMEG/JgXTKwk5cOAAmjZtqjS9SZMm2L9/f6GDIuYtR0xnM0IsWVhssuo3Yp8Cia+LNhhzYWmntWKSVeqVhLx//x4ODspP1+3t7REfH1/ooAgxBouoeGYAmh6XWQqxhOGfa5F4HqPmYkkKpfWyC4hPyfd4MiUWWOsLLDdknxHmd+ctz+Lq2JlhSUZh6ZWEVK5cGSdPnlSafuLECVSqZNkdt1gqcyxmMwvF4IL8Odp5IwrTgx6i7fILpg6l2Ir41OJOJv65aQIh+jHQOd/UN2d6NaSeNGkSxo0bh7i4OHzzzTcAgODgYCxduhQrVqwwZHwkH30PGEMeaBZ7Wf9MErWibqJrjDXde5VghKVaPs2lXBb7yySfMb2SkCFDhiAzMxPz58/H3LlzAQCenp5Yt24dBgwYYNAAibkXaBJCiGocRt05GE0xKeXVu0u50aNHY/To0YiLi4O1tTVKlDBuN7mfs+JxqBW9y2HxyMjIRKtPr4vJb5Z8xgz52JV+Dvoz3bmk+N2S6p2E5OTkICQkBC9evMAPP/wAAHj79i3s7e0pIdHSposvDbas4lAZ0ZAkEoa+m66DBzFeWJk6muKu+J0YzZVxf+fG+B71W6ZEwsDl0nH1OdArCYmMjES7du0QFRWFzMxMtGnTBnZ2dli0aBEyMzOxfv16Q8dZLM079kSr+cwtvyiqhMeDE426nJcAq6DzZ81slxEd0eVHd6yY7LVXH9LQcdUl9P/SA7/4WcbozER/erWOmTBhAho2bIiPHz/C2tpaNr1bt24IDg42WHBEBabyv8XSedEkrBKuRu2PZ/ReBqfY7yVzQPu4qGh6HFPQsV7Qk5xMsXnU31h+5jkS07Ox+pxuHTrKb56x66AXpzruz6JN2wxer5KQixcv4sqVKxAKhQrTPT098ebNG4MERvIUpwNeHxVSH5g6BFJMWFy/EPkYshQy/6LCYlOgWw8h5pV8ykejz24yr63Rhm4Rq9snSRk5BohFf3qVhEgkEpUj5b5+/Rp2dnaFDirXrFmzwOFwFP6qV6+u8TP79u1D9erVYWVlhTp16uD48eMGi8eg9D0XWvY5tHCeHgN29AJS4kwdiVmzjEPE8k75RJFWj39MfAf1MTULa0PC8C4xXfUMlvFjyVMM70j1SkLatm2r0B8Ih8NBSkoKZs6ciW+//dZQsQEAatWqhXfv3sn+Ll26pHbeK1euoE+fPhg6dCju3LmDrl27omvXrnj48KFBYzK24w/eofNq9dupSkG15ovqDtConabt/gEIPQWcnl5wHMaLghSBYniuJSbw8757WHzyGXpvuGbqUIgaeiUhf/zxBy5fvoyaNWsiIyMDP/zwg+xRzKJFiwwaIJ/Ph6urq+yvdOnSauf9888/0a5dO0yePBk1atTA3Llz0aBBA6xevdqgMRmEhhvBMTtu4/7rxLxZ6aZRUWrxLwlhjMH/xBMcvf/W1KGQz9ye/6Jw9cV7penGyhMNecN04bn0XBH1Ic1gyzSpQlwMzDWx16tOiLu7O+7du4c9e/bg3r17SElJwdChQ9G3b1+FiqqGEBoaCjc3N1hZWaFx48bw9/dHhQqqW0tcvXoVkyZNUpjm5+eHoKAgjevIzMxEZmbeOApJSRY6SiwpNs4+jcWG89Im3B3rupk4Gs2McW77XBLvrBwJBDyOQUoQOYXcafIRvP6YhvIlbXA76iOmHpDWyYpY2KFQyzd3lnDMZYklyK2JKZEw/UoRzIzO25CdnQ0vLy+Ehoaib9++WLx4MdauXYthw4YZPAHx9fVFQEAATp48iXXr1iE8PBzNmjVDcrLq2rzR0dFwcXFRmObi4oLo6GiN6/H394eDg4Psz93d3WDbUBTOPo3BmwQ1zzyJRVIaXEwHFnAuJQBikzNQc8ZJ/LjrjqlDUfLVonPYe/MVXulQgnD2aQwGbrmBmKQMI0ZmWOZaOqCO/HkhS0W9TEukcxIiEAiQkVE0B1n79u3x3XffoW7duvDz88Px48eRkJCAvXv3GnQ906ZNQ2Jiouzv1atXBl1+YRX0QxkScLNoAvnEki5yFnaOIZAOM7/vVvEfTn7vf6+QI2E4ev+dQZZX0O9S1zv9lcGhOs0/JOAmzj+Pw4xDllUHT1epmTm49vKDidZe/M5oepXmjB07FosWLUJOTtE27XF0dETVqlURFqa6/birqytiYmIUpsXExMDV1VXjckUiEezt7RX+iH7NAc35J1JcOnPSRaulIYh8n1rwjGak9TL9Rs6NS87EjEMP8eQdPU41pfiUrEJ93txLJ/puum7qEIoVvZKQ//77D4GBgahQoQL8/PzQvXt3hT9jSUlJwYsXL1C2bFmV7zdu3Fips7TTp0+jcePGRoupuLr3KgFfzD+D/WZwR8r0OCupTJ8s4aHvJ4WpnFcJb7BFsBj1OGF4EZeK34OK951prin77+Hvq5Fo/+dFtfOY+wWuIIY8gpVuMix95+hBn1PCXTMZ4dmCTmca6VUx1dHRET169DB0LEp++eUXdOrUCR4eHnj79i1mzpwJHo+HPn36AAAGDBiAcuXKwd/fH4C0J9cWLVpg6dKl6NChA3bv3o2bN29i48aNRo/VmIx9sKVl5WDXjVdoW9MF7k42AIBxu24jPiULv+y7h54+5Y0bQAEKW+Huc7NZsBgVOLH4hncXnhk7kZlj3J4w9SlhMsZX+riQJSB3oj7CRshHNVfD9XVUlAqbQuT/TvT9jmgcq6JSPJJGnZIQiUSCJUuW4Pnz58jKysI333yDWbNmGbxCaq7Xr1+jT58+eP/+PcqUKYOvvvoK165dQ5kyZQAAUVFR4HLzCnOaNGmCnTt34vfff8f//vc/VKlSBUFBQahdu7ZR4isqzMi1MBadeIptVyOx9N9neDynHQBAouG6pe4c8zQ6CXOOPjZChIbyeZwcy8EwTZhTMnMgYQz2VgKDLM8cqDt241My0W3tFQBF1wrEqH3qmAlzHzbBsr8C1fs2K0eCEf/cxBeeThj7deW8uc30q9ApCZk/fz5mzZqF1q1bw9raGitXrkRcXBy2bNlilOB2796t8f2QkBClad999x2+++47o8RjFoxwIF351AdAWlbhalt3Xn3ZEOEQQ9PjmJFIGGrPPAUAeDavHUR8noGDMo1nMapb1r1LKLiyfY5Ygp/33UNDTyf0/9LD0KGZXHFKiorRpuSTt2Hqbk6PP3iHkGdxCHkWp5CExCZn4EKo+fWxpFOdkL///htr167FqVOnEBQUhCNHjmDHjh2QaLptJqrp8CMxdm+nYgOlyFk6FPtHxKdixZnnSEzLNsi6ix0Tn0Sz5AYzi03Sv7mwMcXmawpq7N/JsQfvcOjuW0zXso6NWFK0t566rs1Y0ZnqhrvY5h1ytEmu0rPzbiblH42N23kHL+PMr5K6TklIVFSUQrfsrVu3BofDwdu31KujuVOXNcckZZjkwGz/50WsOBOK/wUZd3A6YxQHv4xL0SnhKu5MUeS+4fwLNFoQjFU6NiMtDF0G+jr1KBrVp5/A4Xvmc27cf9v0lczNmbEfexPVdEpCcnJyYGVlpTBNIBAgO5vuZouMgdP9zZfCDbtALeVm6zcjVLe3lxjlLrLwO+/fR9H4Zul5/PCXkceiMODmF/bkao7Pkv1PPAUALD39XO08YgnDrcgPyMwp+DFj/jvMwpZijPznFrLFDOPNqCOyyPeW0XW5vr9Sfb4xSy49McffpT50qhPCGMOgQYMgEolk0zIyMjBq1CjY2trKpgUGBhouQvJZGrPjNtabOggVdlyPAgDcjPxo4kgsx5N3Sfhpz12F59P5vU1Ih721ACVEejXYA6CcSCw//Ryrz4Xh2zquWNvXR+3n0vPVhVp88in+vhqJY+O/gkcpWzWfKn7y7z9LbuViwaFrT802aptY1ea8REfeNazO6WqoiPSi0y9+4MCBStP69etnsGBIwbR57p2ckQ07LVs0mPpOQN3J4uSjaOBToZs+/YSoXJea6XHJmUhIy0IVFzNqmmnqL0YOA8O7xHRkZEtQsbTuF+XR228h4n2aQvfk8t/Fm4R0NF14FkI+F8GTWhggYqm/LkrH3jn+QPOwDTVmnESzKnkDY64NeQEAWHEmFMt715NNL4qv5OTDaGy7EoFlvb1R1kFzq8MPqVmITc5A9SKIqzjoue4KXB2ssPqHBqYORW+GOhcCwFHR7wAAa2QCMF1jDp2SkK1btxorjs+Pvm3wtfjgh9QsrZMQtev5LG4lpL6YfwYAcHHK17J+UooTfb7K/Oe6xv5nAQB3Z7SBo41QxSfUS8nUXJfi+ktp66ysHAmaLT6n07IN5WJovE7z/301Al3rlzN48+VR228BAGYceoS/BjTUOG+DuacBABFWGmfTgeKXXpxaywB5pZerf1D9flGe8t4kpGPrpXAMbOKp0zlHvs8kQ3091bimrStUHAbhI4Wh14Gs3a+VMYb3hRiIrTD0SaIevkk0QiTFy6sPug+UaOzO0oxF0zE049Aj1Jv9r8HWJZEwnHiQN4ZMQprqrs+NeaHU9VRgrFCKMvcxVaI1eOsNbLoUXqgu4NUdC5aWO1ISYgFik3UbMLCwJ6qDd17jbWLhBymce/QJfOadwaG7bwq9LF3d+nTXY+iWG0X1Azfkagobc2GPp2QdWpWos+/mK3RadQnvErVPggz9XeVfnoQBGdmGGck06O4bjN5x2yDL0lf+r1nf0lDFj5lHb7q6yBFLcDE0DskZxmtw8TwmBQAQpcMoxQDyHYSqd5Sp95+uKAmxALoWFetCVR2Tn/bcM8iyt1yWtrxZcPxJoZajT7ftvTcqt14x9m+TMYaHbxKVKjpqKy0rB0fuvUWSgU9+xj4pFbZVgjbxTd5/Hw/eJGLescIdS4WhKk75/lR0JX89ye0wUJfPKL2n4xdtaRer/NKycvDwTaLBHx1vuPAS/TffMM+B6oxwF8SFaUsqKQn5zFla0Z02boSbZpjto/ffoeOqS+i+7open58W+AA/7rqDsSa+I87v3uuEAuYouoMorYD6JYZkjtdoTdfb5MxsrZojq2UmJwNtw+i8+jI6rrqEU49iCp5ZDVUJzIFPg3bef226x7OxSRnwP/FE4wjY6g4FXb/GRtxnun3AwCgJsXCqnh0X5uSp6kf58E2iQn8eut54FPUdV68NV4t2hZ/kjjis71Dyh+5KO7YyZsmXtuRLyLZcjjBdIPloOpTyn3sN3YOqqpO7vmvY+98rLD5p2JP/k+hktF+hfgRhXRX0s1W37Yb8uaurGwMAYbHSRxpBd4r+ca+xjdt1BxvOv0SPdYrnMvNIEw2LkhBT0eNoskYG3B5uhCdHWoFtx7VI1Jtz2qBhqSqC7LjqEnquN82FnRSeOd7Rf+6mHLiv8NpQF5eX8anIyBZjz39ROtWfMVf15pzW63GutqUB5toCKPemL95EFfuLEiUhFmQKfw887yxCsPAXAMCsI9qPWKvtXaG2z6YNJTY5E+eexhbpOk0lPUtssIqM+qz7WbTqwdsAACmxwO1/gCwVFeWMUJTFkFfqRkmSYS0//RxTDzzAt39qLhXRprm/OVykN154qfH93O0obKRvEz4lbabfZLXfjDa/FWOPoWRolIRYkEZcaVfVPI7hTttFcbgWFO3ggP80f17DiVAsYQYbKKywS9F0vs7KkaDmzJNoMPe0Sfpg6bb2MvxWXMDpx2qen29pBxweB/z7m8blGOqa1HvDVXy/8ZrO+0LT7Ma+YBrz5G6I0HNbgoU8k46U+lHHwSEd3lxQeM2Y5hYyOep+dwqf0f1YN9VFtOf6q0otYhhjCLrzBqFqRl8uenKj6Fp6zeJPKAn5zJnBjY7exBKGr/8IQdvl53X6QaZk5uDkw3d6t2LJJT84WY5YIjv5q/IuMR2MAWlZYq1aVBj6gvr0UynIwTtqOib68OLTjMeU3lK4pBjovPcxLRvXwz/gY1q2QS45jDGDn5S1WVz+7ykxPRsnH75TM7d5c7u3Uqf5DdGM3xD0/doP3HqNVWcVB0B8l5ihcDyuDA7DxD130Wa5YoJmKhZ8ulZL/4EaSJFjWh6CxSVDVidbLIEA0hGAc9vZp2aJtRh3RLr/Gsw5jSyxBD0alMfSXt753tXe+F134ONREuUcrbH9WqSOn9bsla79B2ig0/Ggx7FTmL5YDHFSvRnxASP+uYUPqYqVGE2RYA/aegN3ohKKfsXIOz9ou90rToeiiVdpZGSLMSTgP+zUcX2avveYpAzEJetfn6E8JxYL+JuxQdwRlyV19F6OJj/vK7grguVn1A+QaEyFOoVbWKZCJSGfOUt7fghIK9/pR/rLzi2JOKDH0Ob599aHFOmF776Be1v900hD1JtjflrYkIZuu6mUgOSna4d/qmhzcTdVAqKPGxEfEJOUgerTTxq2LhiHA98Fwei46pLeHdUtE6xDc94D7BD6A5C2hMnt3t8Q1D3C1fj7SPsg/TNztqmv0IcXDAGKrjl7YVBJCLE4mdnKjzMMUfpTuJsP80zmynNiATjq/Dn5SovmmLjIk2hRJ6jR/GCEzm+v03KVexDV6eMqRSdm4KOGZqcF0aYyqS6mBz006PIAKOyo96mZOt+ZcziACxRHqW697DwA4NwvLdUOoqjLY8O/r0boFBMPYmBxRQCAENuQBcOOGaQtxURY9UZ2ONceHQRAaSQC6FwUYRUKlYSYihFP7EbvGVTX+QsZUJ0Pis2Qcxena3F7TFIGhhRQCba4uSSaCN/MvM7TCv4udP+y3qdm4e+rEcgpRO+hmiSm51UWVBVdKSSgLueFwrTBW28gLV+dn/yvDUHX1PNL/2C0L6DViv6x6P7dxRTikYmxaDpGX3zqG6SwTj3SPLJyfjbI208lYdxKqtok1bmiEzMw89BDWZ8p8r7kmq53YV1QEkLMnq244Ecd2vxsF598hrMamgObZ1lG4XVMCzLYslQlfuHxqZhx6BF2/ffKYOuR92u+PjXyC+GMwGHRdNTh5DXlPKeqknAhk2Fj1jHRtiTNXEvcDE1d/TdVX6Ghb7oMUSn84ZtEWR8fpx/H6NSB4Z6bir+jY/ffYd9N5d8WAzBu521suxqJrmsuFypeU6LHMRbEGCUcqnuBlGAxfyOeMA9sEetWhF00cvsFUA5+4YmnCq8NPYBdfrciP+DOq48IjzfMHZole/A6AYCHzp8r6FGapsRRni/3CR6IK6lfj4l7JJHvI6Y0ErFRuBS7xN9gn7il1ssoym3Qd13ynyoL3etxGLtCsbGHRXj0NhEdV10CABwe1xTD/74JAIhY2EHl/DFJGRDyuChpKwQAnMnXjH7sTmm8LaqWUTrn5XYtn1KEwxkYGpWEmAoH+IZ7Gz/x90Of9MKT8w6OaooF2624gGmBDxSmqTuhqPq9N+c+wHf8C5gh+EerWArupyPv/U0XX6KJf7BWyy2IqnoL68+/UDN3wa2L9DnlLjz5FDMOPcJtfSskfowErm9U3UmYwRj3wqVtqy114lO0ryOhKWExdsKpr57rruBG+AcclOte/Bf+HjTghmGJYCMAy24qr059TiiacjSXYqmj7puctPcu3iQU3BMsN/09cGA4fDnKHToee/AOH1ONN0Lu9Zd5lVdzR8vVxHdBMOrPLbjn6+TMHKXzeGEGUDQXlISY0BbhH5jAD0Qb7i2dPxsi+hl3rUaqfC9bzLDrRpTecdlC849c/jow9+hjeM/+V6sTAwDMO/bEYP0LyI+xos2gdfZIxQnhVIzjHTTI+gEgQ0UlWVVexKk5Ga39EjgxGTg712AxGZq2d8SqSqauhCmOgzOJvxe/8bcrTFt0UrH0ylh0H/NI8QOq8gRtkoebkR/Ra8NVZMtdMEpwFH8D2saWkS0x+CjLmmh6NFFQ8tmNd8nQ4SA5Iwdj8pVkqNp39udnAA/2YodA9e9K0zGtaz5oyOb0mihtpxYHzd9XDdt1gDGYdRLi7++PL774AnZ2dnB2dkbXrl3x7JnmQZ8CAgLA4XAU/qysrIooYv24cPJqgnMgwd8Cf8zjb1aar7B3nCoV8hZs86VwpGTmYH2I+hIIbX7W71MydaqQBQD35UZ3la+8qM5g/knU4L7CL4J9Kt835s3okICbqt/I/nQCCzdeZ0jy21VgQlHAiU2nCzlj+GHTdQAM/+PvQB9eMMbzgzCcfxyBwhlYI1ih1WK0PUQrcIq++39TtBzquuYyemkYy0mXOg3xGiqm6rtt+n5O299/mJreS9/LlajxEzXfhOlat0ZTKVtCWjaSMrIRdOeN0mOR/IlsRrYYh+4WZsC9vLjPP1M83s8+Ve4NeebhR4VYV9Ew6yTk/PnzGDt2LK5du4bTp08jOzsbbdu2RWqq5n4i7O3t8e7dO9lfZKT5Z4O56nPC0Jz3AP34hnlkocq+m6+w7UqEQZep+eJW8MnFZ94ZDCpEy5WQZ7FY9q/mBNUQ7eaN1jV4Ia9m71MyMe/oY9XdS+dbdGaOWKeu7h++Ua5Up+qCobBrEt8AS6tjAu8AmnIfYgT/GPwFeYl1A24YOvBugJNuuH4X+vPP4Euu+vGUzPNhjZT8vuMjB63STgAfVI+Z8jIuFTcilPdb7iLUlrqpoL4E89O4PoU4LnX55MM3iag96xQ2XXxZYNKparmnH8fg6z9CdIhNTT8heh4lY7bfxsQ9dzFl/z2N8S888RQTdt/Vax3S29C8hf8epJhgDAm4iYda9ldkD337WjI8s05CTp48iUGDBqFWrVrw9vZGQEAAoqKicOuW5scXHA4Hrq6usj8XF5ciilg/8iUcPBjuGV9aVt5Fd+vlCNwI/wCJhGHy/vuYefgRovN1UaxKd+4FtOUqJgfGug5feK6+23NV5H+QR++/w8qzYRrnN0adEHMx9cB9bLoUjrYrNJeoZOZIUH/OabT51O+CstyLj+b1zTmqefDExJNzgZRo/CQ4gJIwfKXdKpzX2ChYipqcCIXpPbjqt1/ncWr0CUxPz+SSx+G84xiVtBJYWV+vZWXl5J1DUo1YYbE77xKQrf2jVYmEqe1U7tfA+0jLEmPeMWmzUl1LfZefzuvZtBQSwU2P1zA3EKpjU9+C4rn06bHj8Qfqm/5uvPACR+SGejCGp5oGqZQzgn/UqHHowqyTkPwSE6VZnpOTk8b5UlJS4OHhAXd3d3Tp0gWPHmkuksrMzERSUpLCn7HJnyiM8pgFUBobpd+m6won1tSsgk9Qy4TrsVG4XGGaqnO5pvO7OXd29V5uqGy7hCfAnR0GCXj7tUiVI+a6c2KABFVFxYVb571PteQLCv3pu2SkZYnxMj5Vrx4ocxPQAA0laS/jUnDygXHHT9kpnIe2vFvYL5yt9WcK2sMiZIGva2mZ/A4/twAhwp/UVhjXFI18T6u+BuzfYef1KLT/86JSiwuDufyn0qTcYyT/eW3Y3zfRYO5p3In6qPQZ2Ty8Y2gat1fjKjUd43zk4JbVaPATwvVeRmGpK2RccPwp3hfQs68m2sS88IR2x458vyemZjFJiEQiwcSJE9G0aVPUrl1b7XzVqlXDli1bcOjQIWzfvh0SiQRNmjTB69fqu+j29/eHg4OD7M/d3d0Ym6CWRNsxYXRMVvIfs/lrUt9+/By252fBi1OYZ5Sflp1ThLW0dTiBKD7LVd5/Q7fl1dVoFtwNODQGeH6qEMFJ/R70UGlwLCtk4qLoJ4hW1wPE2lcu/JCapXQXn/s45KOK95Spfr/3xmsqpuqfEMckSe+Kb0YqXmQK22pFvvJvbn8LZTjSf2042p9MNe0mEbLwUDQUF0QTtV7eUN5xWK+pm/fY5PwieHJjMJyvPAigvgpb6XH+8Sd48i4Jw/5WUydJDa2/szjli17ufnbjKCa5uU2t1VWWdEQyfhfsQMd3q2DL0aXyOpMlPvYofCXRwpb06lqim4sxhoDL4SofteUqKDZdWpqZC4tJQsaOHYuHDx9i9+7dGudr3LgxBgwYgHr16qFFixYIDAxEmTJlsGHDBrWfmTZtGhITE2V/r14Zp9MldYxREmKPVHATIpSmy6/J+cwEjOAfQ7BoMtYLlmt8nq5KwOW8uw1dizd1teZc3qMWtUOI6+HuqwTlibF5JWfHH7zDj7vuKDzaKsgi/kYcF07DjTDFotlSkCthy9H+JNtg7mn872Bek+v5xx6j0YJgHLzzGvXnnsbPe+8Z7ghK01yMrUnke90vALE69thZmJOspuf9VTmvIeCI4cZRfwGwTX+LJty8bs6nC7aDm/wWOPW7wnzqHqkmpuUlnuU52l2ochM7AGjPvY5NgiVwMMLjLa1FXVd8rSGza8tT/dhcVdLMAQfNuXnHOB+G7922qMhXTtWl/45Dd99i1pHHmsfbkctChMhGLU449ClFNafm7BaRhIwbNw5Hjx7FuXPnUL58eZ0+KxAIUL9+fYSFqa8vIBKJYG9vr/BnqbifToD3rYbDaVOjT2OH5PlhU97dbz1u3j5px/sPu4XzdFrXrCPaJS2GONyXnMqrdKrvoFj6GLPjNo7ce4sN51VXElSlNz8ENbmRqJepe9NrdXbdyEuM/7oYjviUTPy0RzoKaOAdzSVZ8iec/Bfir/8IQWyS4YZkT0zP1qnuhfyzfEUMbbn/6dzZlb53sdqclDud88NO4QI05ORrUszEWvWIueFC3jFUj6vd8SQf1Trhn2jNu4OJ/ANafdbgYh4DW9oWejGqez1lWClcLXut6ftQlUwau58VTfE8U9NaBwBma3mOBICJe+7qEhI2CpfjmOg3DOad1Olz5saskxDGGMaNG4eDBw/i7NmzqFixos7LEIvFePDgAcqWLWuECA1D+8cxmlXjROGxaDB+5AXKpn3BUWwxck2uIx19S2AMMVicIRjtxKNi++JS9HmGyvK9kgs4/zoKuU+1LVHIv5rw+FS1rQo01Y+Qfy/3BP0yPhXes//F1AMP1H1Mibp6SV24l7FRuBxXrX7UelmFofIio+YracBVfMz2ITVTYTwYdResdBV1hAqy6MRThMUqXuRKcZJghzSM5QXBg6PbGCjamsXfhtjkTIUO1vBWu55GC2phwmES4NFB4GOEbFqOWP/j/8yTWFkLLkOcmbTpYEzeL/vuKbw22mkp37Lrf7qJpCTEiMaOHYvt27dj586dsLOzQ3R0NKKjo5GentesbMCAAZg2bZrs9Zw5c/Dvv//i5cuXuH37Nvr164fIyEgMGzbMFJtQpH7nb4cVJxs/C/abOhQF8j+cWpwIbBYsQTWO/p2p6csQJyhdEjAOGC48j8OsQrbVt0U6JvL342P43UItR54VMmWlZKkqBnYTHB6DJ6LBcFVVEnH7b4RZDdC4fG33knyT55JIwhrBCrTg3sNXXP1Gd9X09QzcktfKyw5p6My9LOuYrzAXjtgkbRNA3Y/Am5Ef0XqZcoufWYJtmCzYixPCaQrT+/P+xXLBGlmJqIootFrvQL60B88QhTF4DHN5rf3xDLBvEPCnt2yatq06AONWKs1dth3S8JdgKTpxpYM/8nR4PMRjOVgrWIF+vIJ7QdU5vgLeb8TJq6NjxymaTtQKy6yTkHXr1iExMREtW7ZE2bJlZX979uyRzRMVFYV37/Jq4n/8+BHDhw9HjRo18O233yIpKQlXrlxBzZo1TbEJRjeTv03j3ZA5PPuTjyBQOBOteHewUzjfZPHoI/fkpHJgNA0GbLnxqSUJQ09e3sXk5333lO5w1ZnK342J/ECU3NZCp3XnUnUHHiz6BZdEE1GDo7qSIO/Bbgg4YvTjn1F+87Bi6YSqEjWOmv9r8rtgBzrwbmCbcBFqczW3btCH/COTVYJVWClcg8UC9XXFnrxLQufVl3ApVHM9mfylOSP5x9BdRVNhQ/4SG316JJS/Yu5cQQC68S6jHfeG0mcckIKroh8xk79Nv5UaqOjR5q1iheiIeOU+KzSV0mbmSLDzeuFvYmyRjp/5e1FdxQ3RGP4htOHdwqpPj4h+E+zUernNMs7hW94NzBNsLXSM8tQlX/J7aq8or4fYunK/oa+5d9CSe9eg8RiKWSchjDGVf4MGDZLNExISgoCAANnr5cuXIzIyEpmZmYiOjsaxY8dQv75+7e2LioRxwYUEDTjPIeQot5qwQQZOCaeofI48mH8Ke4Vz1C67Clf3li/GajIMAKJP21eKo+YCHBYM3ArQalnaRKnYW6hhtosLCZbw16MvL+8CbY8UTOXvQlWO6krNnblXMUmuhOrUo2j88Nd1lfPm583N6432+43qe8pUR8Kk8ckr96nlQhfeFZ06cTN0vxPy34gr8h4V1uCqrxxe2JIlAGjJkxahd+Dd+BSH8hn+ZXwq7r9ORL/N1zX2cpmQpvybXSZcr/DaASmYxQ9AXY6mnoUNpwRHuROyfrwzKMv5gMH8U7o3RdaBLiUVD98koqUOnYzlkq+ora/J/D34kR+Ek6Jfld5zytfMWv4GoiA2zLxKIGyRjq3CJQgQLkYpJGKDYBk68XQ/jxiLWSchnwsGYAL/AAJFs7BCsEbp/e9451GNq76JsQsnQe17o/lHNKxX9UW5jIbliZAF27g7gET7Jrnqi6EZpvP/wUCeXJPY7d2BIxNQK18nVEXq7FzgSV5nPi74gAO38y6Kbbi38B3/AuYLtsimzRL8jdH8I/hXNDVvOXKbLZ9IANKLr3w9DsYYnKC6cqP83pOv05OfL+cJlgrWgsdR3N8Nuc9x32oEfuLvAwPQgJNXGXQU/wiuicYqrk/DVURVs97+vNPg5Cv+1/Y69OqDdmMOCZENIaQXe019lOhzs+6GeFTgaO5HI3Cv+tIDbUobZwj+xkDevzgsml7gvPqWXsp/zpvzUmkMKPn3Twsn67WO/F5/VLzg1uRE4Iss5VIYdXJHmy0KDkhBPY60HkUX7iUM4v+rNE9u3ZTClFppW8dPH6rHL9IcbQm542ACPxB+vJsozcl3rom8YoDo9ENJiBlg4GA47ziAvP4P5BmruZqqQ3cqfxfKc9QXP28RLEHtEz2Aa2t1X1++i1s9zgsM5Z/AbIHyCd6Vk78uguof2mz+VgQKZ2h1Z6dTScievsjIFqMv7wyuW43DFPwtGzjMnqNcfFyXo7q1gw/nGUKEP6E5V/Noopz4p7htNQq9eOe0DJChPidUofvlPaK56KFh0LAJ/IMAgADhYoXp+Uulrsp1YqbNBdGRk4rOXP1OYu9T8xIxdeviQoI7ohG4Ixqhoa6D/q5YjcefQs3HczfeRY3vq8OFBHU4L1FTzWMvY+nLD0agcKba9yty8ydd2lx2lX8/9+TGbwKA46L/YVbKHLUlgtrSNRErhYK7K78omogg0Qw0595T+r7dOTEoz4lFp9XS34+mc0VB55FIucS6IscQnfYxrBashPOlGXp9Wr7V0QC+mnoqL87qtWxDoCTEDLACf3IF/yBd8AHNeNpX5nPnxMCJo1wLfDT/CEZo6GypKe9TUfh/m7ReV678N9iqioxzDeQp3qWobr3AMJB/Gg24YQVe5PObwDugdPee37YrEfiNvwMAMIx/ApnZEgBMNvw6APTjnUZpJKo8MUW+T8VO4QJ4cmO0fiw2hx+gYmrespfwpcX8rbm3cVA0E2dEut3RMgZZiYI6Ns8P5/1fy54VNT0+KSxHpMCWkwlbTiZKatUbKYySrOiqLN7jZ/5eHBH9rrB/xsu1XlOl4OEFtEumpaWn0t9NLU642oEbAS3HElFTzPQ2IR0VpymeMyoZ5OKrnUG8k7hlNbrA0bHtP1XU/IZ7R+m9i6KfcEk0EXzkwBXv0Y6nfhyrgs/Weftpk+APjfPmJ0IW1gpWoCcvb1iF6pxX6Mi7hpIPt2j4pHq+3KIZpVpflISYgdIc7QYd0kRTRc/G3EfIn8j8LVhYyDXmb35aMEm+LGS70F/tvM15mp/5JqRlIe5xiOy1NqVF8ieWnwQH4MfV3Ivksnx9WMQkpivtt3mCrdipoX8VkYo6PppYcbKxRrACflzVJ8Hv+BfARw7af6rL4Kzh0ZlqBV/C6l3/Sfb/wfxTshYynbmXcUKo/Py8IIW9G5Qv3i4odsaABfy/cFs0Uu3jLWPWh5B31epHjOUfVpo+SUPrNT/uDVl9FU0KKoLPtVqwEgBwTPSbVvPrqgPvBkYt+kvpBsPQFeJH8w5juWCNyhuHWYK/AUBtkmWnQy+q1sjCNasfUVLFDZo2SuRbl7uOIzv3453Gt7wb+EOuwrT88Xo13HADPpoLSkLMwO+CHbDV0P20Nvc9Xlz1J/pdwvlKNaOVi2M1U7qzzHfWKTDGC0uAB5rHhNBEmO/CUW/OaUhSFB8bVeW8+pRwaaechsdOgLQWvvzJ9MXD6yqTo6rcNzo3hyulIfHswLuBDcLl+Im/D7ZIV0obClPBNv94Qtr49lPCs1K4BjW4qlslaLrk/CRQ37mW/LaoS9iqcfLqQxVUegUAP/DPwZGTij68s/gffweOCv8HEfJ6Wp3O/0fj5wXIwa/8nbghGoOvVdw1G9MG4QqDLq8jT33l5y7cS7BBbkd1ulbzzqNNPZfCmirYjW68y2hcQK/O1/PVbwKAB1bDMIYXZLBY3Djv4ce9oXQs/sTfh4dWw9TeQBSECwmaqWiaLv8bmX1YefvNoQVkYVASUoQi35tu+GRVB7cuTgqnaizili+pLYE0+PP/kiUEddhz4Ow88ING6r3+Z1aDFF735J3H+nwn7H9FU7FLOF86SJwRbD2vvljTlaN+UC5VftKi18sJ/IN4ZDVUabr0pKTfiUdVnyAF0WdN2iZK8idQn3ydgOUawM+ruFzQUuWPw9KcRIzgH0NtbgQ686R1Vkbyjsj6wFBnFO8wRvGPwpmTgK3CJZ8Gtsvbb4J8pW6FvQisEaxQSJLk6fJYSV0rJ3UlP38K1+JPwWosFayDn4bHDzLG7pZUC6ICHiUKOaqP7ykC/W+AhvMUR5w9KJqJDcIVuCsaoTA9t86V/GPx3D2W/zuozHmNk8KpaM/NSxKn8XfmKwXLPa4073cOGKzUPDbVJmkHTNsBJSUhRejs8sE4Lpym9oSTHx85qM6JMsjz7cIeYlW5b3BQKFcxKkF9RbtJ/P3owz+HXZ8eETmqKRbXFwdMobgSUGwF5CFXBFrYC4T8xVTXJX2h4VmstQ6jWNbnKg45UNR3PgwctSc5eR25V3FFNA51OS+0jnG+YDPG8Q7KWi2oXn/eaUqXbR8sl7zkJhHTBLsK/FwLnmL9otWCVbCTa2FQUl3zcj114N1Qm5RuEyxEBU4MfuIX3AHhSDV1ua6Kxqn9TBvebfTgXVSo55SLjxyF7z06sfDd+5dBgtbj5uSSv5DKD0CwSbAE2/R4rGyl4fzbn6fcYkZdHyEOWpR+CjhizOFvRZjVAOwQ5D0yXy5Yi+rcV1gn/FP2uGg4/7jCZ9cLVgBQPO9cUfFdunE+4KnVYJWlwPP52tUj+aCimXlRoSSkCA3mn0JNbiQ6clWNXqrsT8FqnBT9iqH8E4VetwjZ4EKCJtyHSs8tteWdr58S+YO+d8p27BPOgghZcNfxJKOr/BcJQPlCLZuXq+n5uvTnzUeO2n0if9HT1GpIlWEavrfC31PmLeF//B061XPQtZ6KOycOD0XKJTLymnPvY7VwFdw4H7BRuEzrZXfg3cAvgn0IEqmv+S9fJ4RbiARM27oBDbmKdYHa5BuITYRs+MgNh2CI8gF1HUk14z3EBdFPmMDXXJlVE1Ut7rRxTvgznloNlj2yOVDAGEXadCH/n9WYAut75Sf/G85NSBtxnqI1747Kc0FBvueHqH1P1xKTBpzn2C6Yr7E1UG6LlKa8R7BDGipy3ilU+L4hGqPyc6oqx6or6QGAuXzlztF+4GvX6iVHbLqK3HyTrflzk513J8XlaPeF53akpKkfEG3xIMEQ3gn8LtiBhxLPQi8PkNY1qZYRgEwI8H3aToALdONdgjhfblsdBfd+WZHzDuHMMOP79OWdwWT+HizK+R5rhSvVzjddsAObxR1wWjhZqzoyazQsS1ccSApZwpV3MR7BP4Y3rLRWn9KmRCM/bZLgWty8kjEhsg3a4Z38sqRJofpERNP2aboD1kV//hn0V9WTbDHjzpXeTHTgXcNLSVk8i04BhKrndUISOnHzOsBSN5KwPuQv2GsFK9A1a65Cz6CmFCiaBQAI4C7Sav4HVsrDh1hzstCUqzoxG8M7hBCJt8r38qvMfavVfOaGkpCiciWvrXZr7m18r3V/EIbT41Ovf7W5EQZb5jOrQQgSN5G9FiBH4c61BNIwhhV8d3FO9DNqZWw2SEztP91B7BQuKHDeIbwTahOQdtwbsOYY5sKVnx0nHc9FmsdfUaeZihOWtkXcljxEOiBN4C8IJqp9X11FTC/OWzzieOq9Xk133C159zBJi2Nck+rcV0p1D8xF7qOaP3O6q53nttUohderhauU5lHVlXwr7i28ZaXxhHkoTJdPYT3l6njZcjLNcsgHN07hWq38qaKTSgCYItiDc5n1CrVsbZiyaislIUXlY15pgB9Pc9NQYylMUbYmXXl5HVV15F1TaJf+UEXmr84B4SxDhqWVGQL1LSXyV3w1pMK03R/MO4l4OChMq8zRvXt+SyF/1JbnxKMCV/fHfcP4JzQ+Hius8fygQi9Dl/FJTEHVGCu6UPV72ixcCgDwzFC/7VMEexRelzFAlwbmxhbq69uoG9/JoEyYhVASUmRMW7O8GveVxq7fDaUwF9fqRuzwqjhR1Trmay36lgCK5ih04qTgG57hmrbKJ7mW3hzRELrwriCTCYp8vcbc97U4hh+w0JJoKnHNPw6RMZjyV0UVU4tIZo5pi8HVNX8klseLY/7Pfg1Rj0kV+UEDP2e6Vi42BGMmsLvydfhHqebng5KQIiJ6WHDTQEK04a7H44hcRdVbqLFo6nyLGJeuvX/qwj7fEA6qhpQgxRMlIYR8Ru7kq0BIiLbocWnxVSqs4M4TjYWSEEIskKbRcgkhRBfCVNM94qUkhBBCCCEmQUkIIYQQQkyCkhBCCCGEmAQlIYQQQggxCUpCCCGEEGISlIQQQgghxCQsIglZs2YNPD09YWVlBV9fX9y4oTwQkrx9+/ahevXqsLKyQp06dXD8+PEiipQQQggh2jL7JGTPnj2YNGkSZs6cidu3b8Pb2xt+fn6IjVXde9+VK1fQp08fDB06FHfu3EHXrl3RtWtXPHz4sIgjJ4QQQogmHMaYWXfT7+vriy+++AKrV68GAEgkEri7u+PHH3/Er7/+qjR/7969kZqaiqNH84bF/vLLL1GvXj2sX6/dQEBJSUlwcHBAYmIi7O3tDbMhsxwKnocQQggxhVmGG51Yl2uoWZeEZGVl4datW2jdurVsGpfLRevWrXH16lWVn7l69arC/ADg5+endn4AyMzMRFJSksIfIYQQQozLrJOQ+Ph4iMViuLi4KEx3cXFBdHS0ys9ER0frND8A+Pv7w8HBQfbn7u5e+OAJIYQQopFZJyFFZdq0aUhMTJT9vXplhIGavhxr+GUSQoyK8axMHQIhBpfjVMXUIcjwTR2AJqVLlwaPx0NMTIzC9JiYGLi6uqr8jKurq07zA4BIJIJIJCp8wJo0HQ9cW6M4bci/QAVf6f93fg88PwG0mArU6QXYlwW4AuDCEqByK6DCl4qfzc4AJDnAxwgg8jLw7ATQfSNwextwdh5QtR3QcysgtAFS4wFwgPAQYP8Q6ed/iwZCTwN2rkB6AnBzC1DVDzg6UTn2VjOAJuMBLl8az9s70mXv7AWEn5fO8+NtwKkSwOEA4hyAxwfingE5mUDZutJpz44B1zcA7r6A70jpumOfAms/7YM+u4Fd3+etN/8zypRYYOu3gGttoM53QOXWAF8EhCwCQhYAlVoCL0Ok8zYeB8Q9BTquAIS2QPBs6WcCOkjf9/MHGo+R7pvwC9L951ILODNT+n77xcDpGcC3SwDHCsDfXYCy3kC/g4DIDuDygBdngfOLgG4bgFJeQOJrIDMFODZJuq4anaTvh/4r/Z5snYHJocDeAcDjQ0CTH4Erq1Rvb+4+jLwqnbfVdGCBm+L+4PCAYacBtwbA3Z3S/Vm5lTSO5bWUv8dcHZYBns2ANV9IXw84JN13jAFvbgGJr4Ba3aTvMQbMdsz7rJ8/kJUKNBom/W7tXIHkGKCEs/S7z/UhHHh3F6jZVTqdMeDGX9J96FQJ+BgOHBwF9NomXc7RicCXY4CEKKBWd6BM1bx6VDwhMD0ub9lPjwNnZgFd1wECK8C5JpCRAFg5StclkQAxD6TT39wCtvhJv4ve26Wf/xgBHBwtPa6zU6Xfy5Z20v9PCQfE2YA4C+BbgVOijDT23X2l37tbfSAjEajbS3pMtV8MRFwC0t4D3n2k3+f5hXn7VCIGYh4Bt/+WxtJ6lnTfA8C8MtLfsLzxd4EbGwFwgPt7gOHBgKMHkJ2W9/13WAZU7yDd9wCQ9BZYVkP6/6kRgMgeSI0DkqOBqGuA9/fS/X3iVyAnQ/q9KBxHXKDS10CHpcDKeqqPmcEnAI8mea9zv5syNYDRl6W/h4xE4J9u0u0EgIotgIRI6W/x+C95n538ErAtBSS+AZgEcPxU8iyRALGPAUk2sLFl3vwudYBvFwNb20tf//pKup8vLFaOs+9+wKsVcG8nUMIFqNJGOj236mPusRj3FFgrd051rCD9Xr79A7i6Bri6Sro9uSp9DfTcAiyuKH3daMSn7+kTr1bAi2DFWIaekR4vPD6QEgf8UfnTZ0cCbeYAh8cBD/YpfqbNHOlndnwn/a7yaztP+tt8eR5IiweqdwTe3AYCh0nf7xcIPAwEfAYC5Xyk321WCnBiKnB3B9DrH6BmZ+mFnzHg1Q1gS1vl9RQlZuYaNWrExo0bJ3stFotZuXLlmL+/v8r5e/XqxTp27KgwrXHjxmzkyJFarzMxMZEBYImJifoFrU5OtvTflxcYu/2PYZetjbd3GZtpL/1TJyNZ+m9KPGOrGjL2+Ij6ef/bLF3W0pqFi+vFOcZe/ceYRMLY392ky7y0Qrdl5O7bNV8y5l+Bsax01fOlfWQs9Axj4hzV79/axtijIN3WrY33L/LWKZFI42CMsQMjpNu7s0/By8j97jR9f7kS3zIWOEo676nfGfsQwVjCa8aSY/LmWfUFY7Mc875zdR4GSpdzcXnB6zWkiCuMbWghPTYKI/W9dJ9rkpWu/pgxlqgbjK37irHwS9Lj/eIyzfPvH8bYkiqMpScoTk+KzjsuUt+r/7xEwphYzNjDg9J5r29kLDNVcZ60j4ylxEm/8/OL1R9vJ35lbN9g1ft1nqv0M2HBedM2tdH+2BXnMLblW8YODJd+9xnJ0rj39Gfs9Ey57X6Xt8ybWxl7crTgZctLT2Tsz3qMHRyjPo6kaMYur8zbr+kJjGVnSP+f+EZ6vnp6QrofYp8xlvBKGnfUDeXlRd1g7PhUxjKS8qYlvmVsUcW87chdtkTC2NV10mnn/KXf1T89GMtKU15udiZjWzswdmZ2AduboHp61HXNx40edLmGmn0Ssnv3biYSiVhAQAB7/PgxGzFiBHN0dGTR0dGMMcb69+/Pfv31V9n8ly9fZnw+n/3xxx/syZMnbObMmUwgELAHDx5ovU6jJSGmlvpe+xOBNsRi6QXdwAdwoYhzpD9KS5GZKk30CkoEGJOeaGbaM3Z8inbLlkgY+xil/v2cbNUnNVW0iY8Yn6rkOTk273edEq/dcrT53nOypDcacaG6xZgSz1jkNcVpuiQhunhwgLFr6/X/fEHJaVG4uEy6X7b3VH4vKbro4zEAXa6hZv04BpA2uY2Li8OMGTMQHR2NevXq4eTJk7LKp1FRUeBy86q2NGnSBDt37sTvv/+O//3vf6hSpQqCgoJQu3ZtU22C+bBxAsZcA/gGes7N5UqL/80Jlyf9sxRCG6BGR+3m7bNLWvTv9Y1283M4eUXdqvD40j9tiEpoNx8xLlXHto0TUMIVAAOsHbVbjsC64Hl4AqDhEF2ik7ItJf2T12gE8Oq69LGGIdXuXrjPyz9CNJUmEwCPrwDXOsrv2bkoTytmzL6fEFMwSj8hhBBiLOJs6b88gWnj0CQ+FCjpad4xEoPQ5Rpq9iUhhBBCCmAJF/bS5tMig5gPaqJLCCGEEJOgJIQQQgghJkFJCCGEEEJMgpIQQgghhJgEJSGEEEIIMQlKQgghhBBiEpSEEEIIIcQkqJ8QFXL7b0tKSjJxJIQQQohlyb12atMXKiUhKiQnJwMA3N01dHlNCCGEELWSk5Ph4OCgcR7qtl0FiUSCt2/fws7ODhwDjS2QlJQEd3d3vHr1qlh0BU/bY95oe8xXcdoWgLbH3JliexhjSE5Ohpubm8LYbqpQSYgKXC4X5cuXN8qy7e3ti8WBnYu2x7zR9piv4rQtAG2PuSvq7SmoBCQXVUwlhBBCiElQEkIIIYQQk6AkpIiIRCLMnDkTIpHI1KEYBG2PeaPtMV/FaVsA2h5zZ+7bQxVTCSGEEGISVBJCCCGEEJOgJIQQQgghJkFJCCGEEEJMgpIQQgghhJgEJSFFZM2aNfD09ISVlRV8fX1x48YNU4cEf39/fPHFF7Czs4OzszO6du2KZ8+eKcyTkZGBsWPHolSpUihRogR69OiBmJgYhXmioqLQoUMH2NjYwNnZGZMnT0ZOTo7CPCEhIWjQoAFEIhEqV66MgIAAo27bwoULweFwMHHiRIvdljdv3qBfv34oVaoUrK2tUadOHdy8eVP2PmMMM2bMQNmyZWFtbY3WrVsjNDRUYRkfPnxA3759YW9vD0dHRwwdOhQpKSkK89y/fx/NmjWDlZUV3N3dsXjxYoNvi1gsxvTp01GxYkVYW1vDy8sLc+fOVRhbwpy358KFC+jUqRPc3NzA4XAQFBSk8H5Rxr5v3z5Ur14dVlZWqFOnDo4fP27Q7cnOzsbUqVNRp04d2Nraws3NDQMGDMDbt28tcnvyGzVqFDgcDlasWGHR2/PkyRN07twZDg4OsLW1xRdffIGoqCjZ+xZzvmPE6Hbv3s2EQiHbsmULe/ToERs+fDhzdHRkMTExJo3Lz8+Pbd26lT18+JDdvXuXffvtt6xChQosJSVFNs+oUaOYu7s7Cw4OZjdv3mRffvkla9Kkiez9nJwcVrt2bda6dWt2584ddvz4cVa6dGk2bdo02TwvX75kNjY2bNKkSezx48ds1apVjMfjsZMnTxplu27cuME8PT1Z3bp12YQJEyxyWz58+MA8PDzYoEGD2PXr19nLly/ZqVOnWFhYmGyehQsXMgcHBxYUFMTu3bvHOnfuzCpWrMjS09Nl87Rr1455e3uza9eusYsXL7LKlSuzPn36yN5PTExkLi4urG/fvuzhw4ds165dzNramm3YsMGg2zN//nxWqlQpdvToURYeHs727dvHSpQowf7880+L2J7jx4+z3377jQUGBjIA7ODBgwrvF1Xsly9fZjwejy1evJg9fvyY/f7770wgELAHDx4YbHsSEhJY69at2Z49e9jTp0/Z1atXWaNGjZiPj4/CMixle+QFBgYyb29v5ubmxpYvX26x2xMWFsacnJzY5MmT2e3bt1lYWBg7dOiQwjXFUs53lIQUgUaNGrGxY8fKXovFYubm5sb8/f1NGJWy2NhYBoCdP3+eMSY9GQkEArZv3z7ZPE+ePGEA2NWrVxlj0h8Ll8tl0dHRsnnWrVvH7O3tWWZmJmOMsSlTprBatWoprKt3797Mz8/P4NuQnJzMqlSpwk6fPs1atGghS0IsbVumTp3KvvrqK7XvSyQS5urqypYsWSKblpCQwEQiEdu1axdjjLHHjx8zAOy///6TzXPixAnG4XDYmzdvGGOMrV27lpUsWVK2fbnrrlatmkG3p0OHDmzIkCEK07p378769u1rcduT/6JQlLH36tWLdejQQSEeX19fNnLkSINtjyo3btxgAFhkZKTFbs/r169ZuXLl2MOHD5mHh4dCEmJp29O7d2/Wr18/tZ+xpPMdPY4xsqysLNy6dQutW7eWTeNyuWjdujWuXr1qwsiUJSYmAgCcnJwAALdu3UJ2drZC7NWrV0eFChVksV+9ehV16tSBi4uLbB4/Pz8kJSXh0aNHsnnkl5E7jzG2f+zYsejQoYPS+ixtWw4fPoyGDRviu+++g7OzM+rXr4+//vpL9n54eDiio6MVYnFwcICvr6/C9jg6OqJhw4ayeVq3bg0ul4vr16/L5mnevDmEQqHC9jx79gwfP3402PY0adIEwcHBeP78OQDg3r17uHTpEtq3b2+R2yOvKGMvyt+SvMTERHA4HDg6Olrk9kgkEvTv3x+TJ09GrVq1lN63pO2RSCQ4duwYqlatCj8/Pzg7O8PX11fhkY0lne8oCTGy+Ph4iMVihS8aAFxcXBAdHW2iqJRJJBJMnDgRTZs2Re3atQEA0dHREAqFshNPLvnYo6OjVW5b7nua5klKSkJ6errBtmH37t24ffs2/P39ld6ztG15+fIl1q1bhypVquDUqVMYPXo0xo8fj23btinEo+m4io6OhrOzs8L7fD4fTk5OOm2zIfz666/4/vvvUb16dQgEAtSvXx8TJ05E3759LXJ75BVl7OrmMea5JCMjA1OnTkWfPn1kA6BZ2vYsWrQIfD4f48ePV/m+JW1PbGwsUlJSsHDhQrRr1w7//vsvunXrhu7du+P8+fOyOCzlfEej6BIA0hKEhw8f4tKlS6YORS+vXr3ChAkTcPr0aVhZWZk6nEKTSCRo2LAhFixYAACoX78+Hj58iPXr12PgwIEmjk53e/fuxY4dO7Bz507UqlULd+/excSJE+Hm5maR2/O5yM7ORq9evcAYw7p160wdjl5u3bqFP//8E7dv3waHwzF1OIUmkUgAAF26dMFPP/0EAKhXrx6uXLmC9evXo0WLFqYMT2dUEmJkpUuXBo/HU6qVHBMTA1dXVxNFpWjcuHE4evQozp07h/Lly8umu7q6IisrCwkJCQrzy8fu6uqqctty39M0j729PaytrQ2yDbdu3UJsbCwaNGgAPp8PPp+P8+fPY+XKleDz+XBxcbGYbQGAsmXLombNmgrTatSoIav9nhuPpuPK1dUVsbGxCu/n5OTgw4cPOm2zIUyePFlWGlKnTh30798fP/30k6zUytK2R15Rxq5uHmNsW24CEhkZidOnTysMA29J23Px4kXExsaiQoUKsnNDZGQkfv75Z3h6elrc9pQuXRp8Pr/A84OlnO8oCTEyoVAIHx8fBAcHy6ZJJBIEBwejcePGJoxM2qxw3LhxOHjwIM6ePYuKFSsqvO/j4wOBQKAQ+7NnzxAVFSWLvXHjxnjw4IHCDzj3hJX7I2ncuLHCMnLnMeT2t2rVCg8ePMDdu3dlfw0bNkTfvn1l/7eUbQGApk2bKjWXfv78OTw8PAAAFStWhKurq0IsSUlJuH79usL2JCQk4NatW7J5zp49C4lEAl9fX9k8Fy5cQHZ2tsL2VKtWDSVLljTY9qSlpYHLVTzd8Hg82V2dpW2PvKKMvaiOv9wEJDQ0FGfOnEGpUqUU3rek7enfvz/u37+vcG5wc3PD5MmTcerUKYvbHqFQiC+++ELj+cGSzt3UOqYI7N69m4lEIhYQEMAeP37MRowYwRwdHRVqJZvC6NGjmYODAwsJCWHv3r2T/aWlpcnmGTVqFKtQoQI7e/Ysu3nzJmvcuDFr3Lix7P3cZl5t27Zld+/eZSdPnmRlypRR2cxr8uTJ7MmTJ2zNmjVGbaKbS751jKVty40bNxifz2fz589noaGhbMeOHczGxoZt375dNs/ChQuZo6MjO3ToELt//z7r0qWLymah9evXZ9evX2eXLl1iVapUUWh2mJCQwFxcXFj//v3Zw4cP2e7du5mNjY3Bm+gOHDiQlStXTtZENzAwkJUuXZpNmTLFIrYnOTmZ3blzh925c4cBYMuWLWN37tyRtRYpqtgvX77M+Hw+++OPP9iTJ0/YzJkz9WoCqml7srKyWOfOnVn58uXZ3bt3Fc4N8i1DLGV7VMnfOsbSticwMJAJBAK2ceNGFhoaKms6e/HiRdkyLOV8R0lIEVm1ahWrUKECEwqFrFGjRuzatWumDokBUPm3detW2Tzp6elszJgxrGTJkszGxoZ169aNvXv3TmE5ERERrH379sza2pqVLl2a/fzzzyw7O1thnnPnzrF69eoxoVDIKlWqpLAOY8mfhFjathw5coTVrl2biUQiVr16dbZx40aF9yUSCZs+fTpzcXFhIpGItWrVij179kxhnvfv37M+ffqwEiVKMHt7ezZ48GCWnJysMM+9e/fYV199xUQiEStXrhxbuHChwbclKSmJTZgwgVWoUIFZWVmxSpUqsd9++03hombO23Pu3DmVv5WBAwcWeex79+5lVatWZUKhkNWqVYsdO3bMoNsTHh6u9txw7tw5i9seVVQlIZa2PZs3b2aVK1dmVlZWzNvbmwUFBSksw1LOdxzG5LosJIQQQggpIlQnhBBCCCEmQUkIIYQQQkyCkhBCCCGEmAQlIYQQQggxCUpCCCGEEGISlIQQQgghxCQoCSGEEEKISVASQgghhBCToCSEEGK2OBwOgoKCTB0GZs2ahXr16pk6DEKKHUpCCPmMxcXFYfTo0ahQoQJEIhFcXV3h5+eHy5cvmzo0g4iIiACHw8Hdu3dNHQohRAW+qQMghJhOjx49kJWVhW3btqFSpUqIiYlBcHAw3r9/b+rQCCGfASoJIeQzlZCQgIsXL2LRokX4+uuv4eHhgUaNGmHatGno3LmzbL5ly5ahTp06sLW1hbu7O8aMGYOUlBTZ+wEBAXB0dMTRo0dRrVo12NjYoGfPnkhLS8O2bdvg6emJkiVLYvz48RCLxbLPeXp6Yu7cuejTpw9sbW1Rrlw5rFmzRmPMr169Qq9eveDo6AgnJyd06dIFERERWm9zSEgIOBwOgoOD0bBhQ9jY2KBJkyZKw6IvXLgQLi4usLOzw9ChQ5GRkaG0rE2bNqFGjRqwsrJC9erVsXbtWtl7Q4YMQd26dZGZmQkAyMrKQv369TFgwACtYyXks2DQ4fAIIRYjOzublShRgk2cOJFlZGSonW/58uXs7NmzLDw8nAUHB7Nq1aqx0aNHy97funUrEwgErE2bNuz27dvs/PnzrFSpUqxt27asV69e7NGjR+zIkSNMKBSy3bt3yz7n4eHB7OzsmL+/P3v27BlbuXIl4/F47N9//5XNA4AdPHiQMcZYVlYWq1GjBhsyZAi7f/8+e/z4Mfvhhx9YtWrVFEbjlZc7IuydO3cYY3mjk/r6+rKQkBD26NEj1qxZM9akSRPZZ/bs2cNEIhHbtGkTe/r0Kfvtt9+YnZ0d8/b2ls2zfft2VrZsWXbgwAH28uVLduDAAebk5MQCAgIYY9Kh2CtVqsQmTpzIGGPsl19+YZ6eniwxMVG7L4eQzwQlIYR8xvbv389KlizJrKysWJMmTdi0adPYvXv3NH5m3759rFSpUrLXW7duZQBYWFiYbNrIkSOZjY2NwlDofn5+bOTIkbLXHh4erF27dgrL7t27N2vfvr3stXwS8s8//7Bq1aoxiUQiez8zM5NZW1uzU6dOqYxVXRJy5swZ2TzHjh1jAFh6ejpjjLHGjRuzMWPGKCzH19dXIQnx8vJiO3fuVJhn7ty5rHHjxrLXV65cYQKBgE2fPp3x+Xx28eJFlTES8jmjxzGEfMZ69OiBt2/f4vDhw2jXrh1CQkLQoEEDBAQEyOY5c+YMWrVqhXLlysHOzg79+/fH+/fvkZaWJpvHxsYGXl5estcuLi7w9PREiRIlFKbFxsYqrL9x48ZKr588eaIy1nv37iEsLAx2dnYoUaIESpQoAScnJ2RkZODFixc6bXfdunVl/y9btiwAyGJ78uQJfH191caZmpqKFy9eYOjQobI4SpQogXnz5inE0bhxY/zyyy+YO3cufv75Z3z11Vc6xUjI54AqphLymbOyskKbNm3Qpk0bTJ8+HcOGDcPMmTMxaNAgREREoGPHjhg9ejTmz58PJycnXLp0CUOHDkVWVhZsbGwAAAKBQGGZHA5H5TSJRKJ3nCkpKfDx8cGOHTuU3itTpoxOy5KPjcPhAIDWseXWh/nrr7+UkhUejyf7v0QiweXLl8Hj8RAWFqZTfIR8LqgkhBCioGbNmkhNTQUA3Lp1CxKJBEuXLsWXX36JqlWr4u3btwZb17Vr15Re16hRQ+W8DRo0QGhoKJydnVG5cmWFPwcHB4PFVKNGDVy/fl1tnC4uLnBzc8PLly+V4qhYsaJsviVLluDp06c4f/48Tp48ia1btxosRkKKC0pCCPlMvX//Ht988w22b9+O+/fvIzw8HPv27cPixYvRpUsXAEDlypWRnZ2NVatW4eXLl/jnn3+wfv16g8Vw+fJlLF68GM+fP8eaNWuwb98+TJgwQeW8ffv2RenSpdGlSxdcvHgR4eHhCAkJwfjx4/H69WuDxTRhwgRs2bIFW7duxfPnzzFz5kw8evRIYZ7Zs2fD398fK1euxPPnz/HgwQNs3boVy5YtAwDcuXMHM2bMwKZNm9C0aVMsW7YMEyZMwMuXLw0WJyHFASUhhHymSpQoAV9fXyxfvhzNmzdH7dq1MX36dAwfPhyrV68GAHh7e2PZsmVYtGgRateujR07dsDf399gMfz888+4efMm6tevj3nz5mHZsmXw8/NTOa+NjQ0uXLiAChUqoHv37qhRo4as+ay9vb3BYurduzemT5+OKVOmwMfHB5GRkRg9erTCPMOGDcOmTZuwdetW1KlTBy1atEBAQAAqVqyIjIwM9OvXD4MGDUKnTp0AACNGjMDXX3+N/v37KzRTJuRzx2GMMVMHQQj5/Hh6emLixImYOHGiqUMhhJgIlYQQQgghxCQoCSGEEEKISdDjGEIIIYSYBJWEEEIIIcQkKAkhhBBCiElQEkIIIYQQk6AkhBBCCCEmQUkIIYQQQkyCkhBCCCGEmAQlIYQQQggxCUpCCCGEEGIS/wepAi9FFC3oxAAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "RAndomforest"
      ],
      "metadata": {
        "id": "gS5lCToaSq9N"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.ensemble import RandomForestRegressor\n",
        "final_model = RandomForestRegressor(\n",
        "    max_depth=30,\n",
        "    max_features='log2',\n",
        "    min_samples_leaf=4,\n",
        "    min_samples_split=10,\n",
        "    n_estimators=100,\n",
        "    random_state=41\n",
        ")\n",
        "\n",
        "# Fit the model\n",
        "final_model.fit(X_train_scaled, y_train_scaled.ravel())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "NeDWwibpSOfL",
        "outputId": "7e0ca3ad-69d6-411a-9589-a2fc20d38433"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RandomForestRegressor(max_depth=30, max_features='log2', min_samples_leaf=4,\n",
              "                      min_samples_split=10, random_state=41)"
            ],
            "text/html": [
              "<style>#sk-container-id-17 {color: black;}#sk-container-id-17 pre{padding: 0;}#sk-container-id-17 div.sk-toggleable {background-color: white;}#sk-container-id-17 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-17 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-17 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-17 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-17 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-17 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-17 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-17 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-17 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-17 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-17 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-17 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-17 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-17 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-17 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-17 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-17 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-17 div.sk-item {position: relative;z-index: 1;}#sk-container-id-17 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-17 div.sk-item::before, #sk-container-id-17 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-17 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-17 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-17 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-17 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-17 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-17 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-17 div.sk-label-container {text-align: center;}#sk-container-id-17 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-17 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-17\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestRegressor(max_depth=30, max_features=&#x27;log2&#x27;, min_samples_leaf=4,\n",
              "                      min_samples_split=10, random_state=41)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-20\" type=\"checkbox\" checked><label for=\"sk-estimator-id-20\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomForestRegressor</label><div class=\"sk-toggleable__content\"><pre>RandomForestRegressor(max_depth=30, max_features=&#x27;log2&#x27;, min_samples_leaf=4,\n",
              "                      min_samples_split=10, random_state=41)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "evaluate_model(final_model, X_train_scaled, X_test_scaled, y_train, y_test, scaler_y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 704
        },
        "id": "RKDy_SkK2Rdc",
        "outputId": "ccd35303-81e9-40ec-f16c-a0381b1fbe9e"
      },
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training MSE: 0.16, Training MAE: 0.16\n",
            "Testing MSE: 0.36, Testing MAE: 0.25\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "KNN"
      ],
      "metadata": {
        "id": "0twJIIjmSsZE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.neighbors import KNeighborsRegressor\n",
        "\n",
        "final_model = KNeighborsRegressor(n_neighbors=3)  # You can adjust n_neighbors\n",
        "final_model.fit(X_train_scaled, y_train_scaled.ravel())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 94
        },
        "id": "aFkLHeEWStSg",
        "outputId": "2d75e6af-a0d7-4f46-8a8b-be2fce611ec6"
      },
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "KNeighborsRegressor(n_neighbors=3)"
            ],
            "text/html": [
              "<style>#sk-container-id-18 {color: black;}#sk-container-id-18 pre{padding: 0;}#sk-container-id-18 div.sk-toggleable {background-color: white;}#sk-container-id-18 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-18 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-18 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-18 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-18 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-18 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-18 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-18 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-18 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-18 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-18 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-18 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-18 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-18 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-18 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-18 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-18 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-18 div.sk-item {position: relative;z-index: 1;}#sk-container-id-18 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-18 div.sk-item::before, #sk-container-id-18 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-18 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-18 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-18 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-18 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-18 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-18 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-18 div.sk-label-container {text-align: center;}#sk-container-id-18 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-18 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-18\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KNeighborsRegressor(n_neighbors=3)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-21\" type=\"checkbox\" checked><label for=\"sk-estimator-id-21\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">KNeighborsRegressor</label><div class=\"sk-toggleable__content\"><pre>KNeighborsRegressor(n_neighbors=3)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "evaluate_model(final_model, X_train_scaled, X_test_scaled, y_train, y_test, scaler_y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 704
        },
        "id": "qLTZoU7P2U_F",
        "outputId": "474cac25-98eb-4a56-e0e8-e94625986951"
      },
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training MSE: 0.15, Training MAE: 0.16\n",
            "Testing MSE: 0.38, Testing MAE: 0.24\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "SVM"
      ],
      "metadata": {
        "id": "Sm-6AzBe0HUf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.svm import SVR\n",
        "\n",
        "final_model = SVR(\n",
        "    kernel='rbf',          # Radial basis function kernel\n",
        "    C=1.0,                 # Regularization parameter\n",
        "    epsilon=0.1            # Epsilon in the epsilon-SVR model\n",
        ")\n",
        "final_model.fit(X_train_scaled, y_train_scaled.ravel())\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 94
        },
        "id": "tAVNrDNX0H5h",
        "outputId": "0b46e90d-a8da-46a9-8e60-6da6ecc95623"
      },
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SVR()"
            ],
            "text/html": [
              "<style>#sk-container-id-19 {color: black;}#sk-container-id-19 pre{padding: 0;}#sk-container-id-19 div.sk-toggleable {background-color: white;}#sk-container-id-19 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-19 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-19 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-19 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-19 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-19 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-19 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-19 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-19 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-19 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-19 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-19 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-19 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-19 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-19 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-19 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-19 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-19 div.sk-item {position: relative;z-index: 1;}#sk-container-id-19 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-19 div.sk-item::before, #sk-container-id-19 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-19 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-19 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-19 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-19 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-19 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-19 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-19 div.sk-label-container {text-align: center;}#sk-container-id-19 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-19 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-19\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>SVR()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-22\" type=\"checkbox\" checked><label for=\"sk-estimator-id-22\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SVR</label><div class=\"sk-toggleable__content\"><pre>SVR()</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 69
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "evaluate_model(final_model, X_train_scaled, X_test_scaled, y_train, y_test, scaler_y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 704
        },
        "id": "Lr0siNkY2ZsQ",
        "outputId": "a2ed8d1f-3f31-47f0-9846-1dfb8639defb"
      },
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training MSE: 0.31, Training MAE: 0.20\n",
            "Testing MSE: 0.41, Testing MAE: 0.23\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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0CqxPnTp1AECqDY0ybt++jfnz5+Pu3bsFfkCSkpKUSuKAL99F3bp1C7xXr1493Lp1S2qagYFBgdsMFStWLNA+Qx72VXuYogQHByMpKalA24g8eQ03O3TogH79+mHhwoVYu3YtOnbsCA8PD/z4448QCARKLTO/r5NxQHp94+LikJGRgVq1ahUoJ2uaPIMHD8bgwYORnJyM+/fvw9vbG/v370fPnj3x7NkzGBgYIDg4GC9fvpR7m0eZRqx530NZHhuFkpAy5OrVq4iOjsbBgwdx8ODBAu/v27dPkoQUl7yDQigUgsvlSl7v3bsXI0eOhIeHB2bNmgUrKytwuVx4enpK2lkoa9CgQRg1ahQeP36MJk2a4PDhw+jcubPUff/27dsjNDQUJ0+exKVLl7B9+3asXbsWXl5eGDt2bJHLaNSoEdzc3Iosl/+KFxDX9nA4HJw/f15qO+SpUKGCAmtYsko7xsqVK6u8LQFg5syZcHd3l/kZZX5ASktoaCg6d+6MevXqYc2aNbC1tQWfz8e5c+ewdu1ayXqVJFnfq6IqVaqkcLKSRyQSwcrKSm4j+LwfZA6Hg6NHj+LevXs4ffo0Ll68iNGjR2P16tW4d++eyvuevPVVNplSlKmpKbp06YIuXbpAX18fu3fvxv3799GhQweIRCI0atQIa9askflZZdpSff78GUZGRgWOjbKEkpAyZN++fbCyssKmTZsKvOfj44Pjx4/Dy8sLhoaGcHR0xLNnzwqdX2HZd8WKFWUO0hQRESF1VXn06FHUrFkTPj4+UvMrTpdhDw8PTJgwQXJL5s2bNzK7zVpYWGDUqFEYNWoUUlNT0b59eyxYsEChJERVjo6OYIzBwcFBcjUti52dHQDxFWT+7nc5OTkICwuDs7Oz3M/mbV9Vv7/SiFEd8tZTX1+/yCRGkf1ZHpFIhLdv30ptizdv3gAQ92CRR972PX36NLKysnDq1CmpK3RZ1fCKXuHmfRevX78u0F3z9evXkvfVoV69elI1qYpwdHTElStX0KZNG4V+MFu1aoVWrVph6dKl2L9/P4YMGYKDBw9i7NixJXLVb2VlBQMDA4SEhBR4T9Y0ZTRv3hy7d+9GdHQ0APG2CAoKQufOnYtcl6LeDwsLg5OTU7Hi03bUJqSMyMjIgI+PD77//nv079+/wN+UKVOQkpIi6drYr18/BAUFyRy5Mu/qIW/MC1nJhqOjI+7du4fs7GzJtDNnzhTo4pl3hZL/iuT+/fu4e/euyutqbm4Od3d3HD58GAcPHgSfz4eHh4dUmYSEBKnXFSpUQK1atUp8GOS+ffuCy+Vi4cKFBa7CGGOSuJo3bw5LS0t4eXlJbUNvb+8iR+C0tLRE+/btsXPnTkRGRhZYRh55319pxKgOVlZW6NixI/755x/JCT6/+Ph4yf8V2Z8Lk9e1O6/8xo0boa+vj86dO8v9jLztK2ufT0pKwq5du2TOQ5Ft2bx5c1hZWcHLy0tqHz5//jxevnyJHj16FDkPRbm6uuLZs2dKHSsDBgyAUCiU3CLNLzc3V7KOnz9/LvB95PWQy1uekZERANnnHVVxuVy4ubnhxIkTiIqKkkwPCQnB+fPni/x8enq63HNW3ufzbpUNGDAAHz58wLZt2wqUzcjIQFpamuR1Ud9/QECA0j0SdQ3VhJQRp06dQkpKCnr16iXz/VatWsHS0hL79u3DwIEDMWvWLBw9ehQ//PADRo8eDRcXF3z69AmnTp2Cl5cXnJ2d4ejoCHNzc3h5ecHExATGxsZo2bIlHBwcMHbsWBw9ehTdunXDgAEDEBoair179xboYvb999/Dx8cHffr0QY8ePRAWFgYvLy/Ur18fqampKq/vwIEDMXToUGzevBnu7u4F2hjUr18fHTt2lPS19/f3x9GjR6UaIJYER0dHLFmyBHPmzEF4eDg8PDxgYmKCsLAwHD9+HOPHj8fMmTOhr6+PJUuWYMKECfj2228xcOBAhIWFYdeuXQq1t1i/fj3atm2LZs2aYfz48XBwcEB4eDjOnj0rGWbfxcUFAPDHH39g0KBB0NfXR8+ePUstRnXYtGkT2rZti0aNGmHcuHGoWbMmYmNjcffuXbx//x5BQUEAoND+LI+BgQEuXLiAESNGoGXLljh//jzOnj2L//3vf4V235S3fbt27Qo+n4+ePXtiwoQJSE1NxbZt22BlZVUgmXJxccGWLVuwZMkS1KpVC1ZWVjIHptLX18eKFSswatQodOjQAYMHD5Z00bW3t8cvv/yiyuaVqXfv3li8eDGuX7+u8O3bDh06YMKECfD09MTjx4/RtWtX6OvrIzg4GEeOHMHff/+N/v37Y/fu3di8eTP69OkDR0dHpKSkYNu2bTA1NcV3330HQHxbrn79+jh06BDq1KkDCwsLNGzYUOU2UHkWLFiAS5cuoU2bNpg0aRKEQiE2btyIhg0bFvloivT0dLRu3RqtWrVCt27dYGtri8TERJw4cQI3b96Eh4cHmjZtCgAYNmwYDh8+jIkTJ+LatWto06YNhEIhXr16hcOHD+PixYuSBu4uLi64cuUK1qxZAxsbGzg4OEgetfHo0SN8+vQJvXv3LtZ6a71S7o1DSkjPnj2ZgYEBS0tLk1tm5MiRTF9fn338+JExxlhCQgKbMmUKq1atGuPz+ax69epsxIgRkvcZY+zkyZOsfv36km5s+bs3rl69mlWrVo0JBALWpk0b5u/vL3PI8WXLljE7OzsmEAhY06ZN2ZkzZ9iIESOYnZ2dVHxQYtj25ORkZmhoyACwvXv3Fnh/yZIlrEWLFszc3JwZGhqyevXqsaVLl7Ls7OxC55vXNfLIkSOFlsvrKpi/C2d+x44dY23btmXGxsbM2NiY1atXj02ePJm9fv1aqtzmzZuZg4MDEwgErHnz5uzGjRsFtqGsrqWMMfbs2TPWp08fZm5uzgwMDFjdunXZ3LlzpcosXryYVatWjenp6RXoTqrOGOWxs7Mrsqt03vqtWrVK5vuhoaFs+PDhrEqVKkxfX59Vq1aNff/99+zo0aNS5Yran+V10TU2NmahoaGsa9euzMjIiFlbW7P58+cXGDJd1v4pb/ueOnWKNW7cmBkYGDB7e3u2YsUKtnPnzgLfQUxMDOvRowczMTGR6vb8dRfdPIcOHWJNmzZlAoGAWVhYsCFDhrD3799Llclbp6/J6t4qT+PGjdmYMWPkvv91F908W7duZS4uLszQ0JCZmJiwRo0asdmzZ7OoqCjGGGMBAQFs8ODBrEaNGkwgEDArKyv2/fffM39/f6n53Llzh7m4uDA+ny+13eV10Z08eXKBWGQNI+Dr68uaNm3K+Hw+c3R0ZNu3b2e//vorMzAwKHR75OTksG3btjEPDw/JuczIyIg1bdqUrVq1qsAwBNnZ2WzFihWsQYMGTCAQsIoVKzIXFxe2cOFClpSUJCn36tUr1r59e8m5LH+8v/32G6tRo0aZH7adw1gJtdwhhBAtN3LkSBw9erRYtXJl0Z49ezB58mRERkbK7MlUlnh4eBSrO39JyMrKgr29PX7//XdMmzZN0+GUKGoTQgghRMqQIUNQo0YNmY3cdVlGRobU6+DgYJw7d07qURPaYNeuXdDX15f7bKWyhGpCCCHlFtWElC9Vq1bFyJEjUbNmTURERGDLli3IyspCYGCg3HFzSMmihqmEEELKhW7duuHAgQOIiYmBQCCAq6srli1bRgmIBlFNCCGEEEI0gtqEEEIIIUQjKAkhhBBCiEZQmxAZRCIRoqKiYGJiUqYfHEQIIYSoG2MMKSkpsLGxgZ5e4XUdlITIEBUVpdRDhgghhBAi7d27d6hevXqhZSgJkcHExASAeAOamppqOBpCCCFEdyQnJ8PW1lbyW1oYSkJkyLsFY2pqSkkIIYQQogJFmjNQw1RCCCGEaAQlIYQQQgjRCEpCCCGEEKIR1CaEkDKIMYbc3FwIhUJNh0JUwOVywePxaIgAUuZREkJIGZOdnY3o6Gikp6drOhRSDEZGRqhatSr4fL6mQyGkxFASQkgZIhKJEBYWBi6XCxsbG/D5fLqa1jGMMWRnZyM+Ph5hYWGoXbt2kQM+EaKrKAkhpAzJzs6GSCSCra0tjIyMNB0OUZGhoSH09fURERGB7OxsGBgYaDokoqPWXn6DuJQsLOvTUCsvSDSaXt+4cQM9e/aEjY0NOBwOTpw4IfX+yJEjweFwpP66detW5Hw3bdoEe3t7GBgYoGXLlnjw4EEJrQEh2omunHUffYdEHf72DcaBB5F4E5uq6VBk0uhenpaWBmdnZ2zatElumW7duiE6Olryd+DAgULneejQIcyYMQPz589HQEAAnJ2d4e7ujri4OHWHTwghhOiE7FyRpkOQSaO3Y7p3747u3bsXWkYgEKBKlSoKz3PNmjUYN24cRo0aBQDw8vLC2bNnsXPnTvz+++/FipcQQggh6qP19X1+fn6wsrJC3bp1MWnSJCQkJMgtm52djUePHsHNzU0yTU9PD25ubrh7967cz2VlZSE5OVnqjxBCAMi8VUwIUQ+tTkK6deuGf//9F76+vlixYgWuX7+O7t27yx374OPHjxAKhbC2tpaabm1tjZiYGLnL8fT0hJmZmeSPnqBLiGbcvXsXXC4XPXr0UOpz9vb2WLduXckERQgpMVqdhAwaNAi9evVCo0aN4OHhgTNnzuDhw4fw8/NT63LmzJmDpKQkyd+7d+/UOn9CiGJ27NiBn3/+GTdu3EBUVJSmwyGElDCtTkK+VrNmTVSuXBkhISEy369cuTK4XC5iY2OlpsfGxhbarkQgEEiemEtPziVlCWMM6dm5GvljjCkVa2pqKg4dOoRJkyahR48e8Pb2lnr/9OnT+Oabb2BgYIDKlSujT58+AICOHTsiIiICv/zyi6QXHQAsWLAATZo0kZrHunXrYG9vL3n98OFDdOnSBZUrV4aZmRk6dOiAgIAApbczIUQ1OjVOyPv375GQkICqVavKfJ/P58PFxQW+vr7w8PAAIB68ydfXF1OmTCnFSAnRDhk5QtSfd1Ejy36xyB1GfMVPMYcPH0a9evVQt25dDB06FNOnT8ecOXPA4XBw9uxZ9OnTB3/88Qf+/fdfZGdn49y5cwAAHx8fODs7Y/z48Rg3bpxSMaakpGDEiBHYsGEDGGNYvXo1vvvuOwQHB8PExESpeRFClKfRJCQ1NVWqViMsLAyPHz+GhYUFLCwssHDhQvTr1w9VqlRBaGgoZs+ejVq1asHd3V3ymc6dO6NPnz6SJGPGjBkYMWIEmjdvjhYtWmDdunVIS0uT9JYhhGinHTt2YOjQoQDE7cGSkpJw/fp1dOzYEUuXLsWgQYOwcOFCSXlnZ2cAgIWFBbhcLkxMTBTuSZcjFCExPQftO3QEj/ulQnjr1q0wNzfH9evX8f3336tx7Qghsmg0CfH390enTp0kr2fMmAEAGDFiBLZs2YInT55g9+7dSExMhI2NDbp27YrFixdDIBBIPhMaGoqPHz9KXg8cOBDx8fGYN28eYmJi0KRJE1y4cKFAY1VCygNDfS5eLHIvumAJLVtRr1+/xoMHD3D8+HEAAI/Hw8CBA7Fjxw507NgRjx8/VrqWozDhH9OQkSPE28gP2L7OE35+foiLi4NQKER6ejoiIyPVtixCiHwaTUI6duxY6H3jixeLrkYODw8vMG3KlCl0+4UQiLuXKnNLRFN27NiB3Nxc2NjYSKYxxiAQCLBx40YYGhoqPU89Pb0C55ecnBwA4ttUADBj8nhkpyXh77//hp2dHQQCAVxdXZGdnV2MtSFE+zAo10artOhUw1RCSNmTm5uLf//9F6tXr8bjx48lf0FBQbCxscGBAwfQuHFj+Pr6yp0Hn88v0HXf0tISMTExUonI48ePpco89r+PqVOn4rvvvkODBg0gEAikalYJISVL+y+RCCFl2pkzZ/D582eMGTMGZmZmUu/169cPO3bswKpVq9C5c2c4Ojpi0KBByM3Nxblz5/Dbb78BEI8TcuPGDQwaNAgCgQCVK1dGx44dER8fj5UrV6J///64cOECzp8/L9X7rYZDTezZswfNmzdHcnIyZs2apVKtCyFENVQTQgjRqB07dsDNza1AAgKIkxB/f39YWFjgyJEjOHXqFJo0aYJvv/1W6sGUixYtQnh4OBwdHWFpaQkAcHJywubNm7Fp0yY4OzvjwYMHmDlzptT8F6zagM+fP6NZs2YYNmwYpk6dCisrq5JdYUKIBIcp25m/HEhOToaZmRmSkpJozBCiUzIzMxEWFgYHBwd6/HshnrxPlPy/cXVzjcVRGPouiTrY/34WAHBqSptS29eV+Q2lmhBCCCGEaAQlIYQQQgjRCEpCCCGEEKIRlIQQQgghRCMoCSGEEEKIRlASQgghhJRx2toPlpIQQgghhGgEJSGEEEII0QhKQgghhBCiEZSEEELKlZEjR2L6mCGS1x07dsT06dNLPQ4/Pz9wOBwkJiaW+rIJ0RaUhBBCtMLIkSPB4XDA4XDA5/NRq1YtLFq0CLm5uSW6XB8fHyxevFihspQ4EKJe9BRdQojW6NatG3bt2oWsrCycO3cOkydPhr6+PubMmSNVLjs7G3w+Xy3LtLCwUMt8CCHKo5oQQsoyxoDsNM38qdAnUCAQoEqVKrCzs8OkSZPg5uaGU6dOYeTIkfDw8MDSpUthY2ODunXrAgDevXuHAQMGwNzcHBYWFujduzfCw8Ml8xMKhZgxYwbMzc1RqVIlzJ49G18/s/Pr2zFZWVn47bffYGtrC4FAgFq1amHHjh0IDw9Hp06dAAAVK1YEh8PByJEjAQAikQienp5wcHCAoaEhnJ2dcfToUanlnDt3DnXq1IGhoSE6deokFSch5RXVhBBSluWkA8tsNLPs/0UBfONizcLQ0BAJCQkAAF9fX5iamuLy5csAgJycHLi7u8PV1RU3b94Ej8fDkiVL0K1bNzx58gR8Ph+rV6+Gt7c3du7cCScnJ6xevRrHjx9Hc9d2cpc5fPhw3L17F+vXr4ezszPCwsLw8eNH2Nra4tixY+jXrx9ev34NU1NTGBoaAgA8PT2xd+9eeHl5oXbt2rhx4waGDh0KS0tLdOjQAe/evUPfvn0xefJkjB8/Hv7+/vj111+LtW0IKQsoCSGEaB3GGHx9fXHx4kX8/PPPiI+Ph7GxMbZv3y65DbN3716IRCJs374dHA4HALBr1y6Ym5vDz88PXbt2xbp16zBnzhz07dsXAODl5YWLFy/KXe6bN29w+PBhXL58GW5ubgCAmjVrSt7Pu3VjZWUFc3NzAOKak2XLluHKlStwdXWVfObWrVv4559/0KFDB2zZsgWOjo5YvXo1AKBu3bp4+vQpVqxYocatRojuoSSEkLJM30hcI6GpZSvpzJkzqFChAnJyciASifDjjz9iwYIFmDx5Mho1aiTVDiQoKAghISEwMTGRmkdmZiZCQ0ORlJSE6OhotGzZUvIej8dD8+bNkZSeLXP5jx8/BpfLRYcOHRSOOSQkBOnp6ejSpYvU9OzsbDRt2hQA8PLlS6k4AEgSFkLKM0pCyoiwj2n488RTTO5YC61rVdZ0OERbcDjFviVSmjp16oQtW7aAz+fDxsYGPN6XU5SxsfR6pKamwsXFBfv27SswH0tLS5WWn3d7RRmpqakAgLNnz6JatWpS7wkEApXiIETdtHTUdkpCyoqf9gXgZXQybockIHx5D02HQ4hKjI2NUatWLYXKNmvWDIcOHYKVlRVMTU1llqlatSru37+P9u3bAwByc3Px6NEj1HJqJLN8o0aNIBKJcP36dcntmPzyamKEQqFkWv369SEQCBAZGSm3BsXJyQmnTp2Smnbv3r2iV5KQMo56x5QR8SmZmg6BkFI1ZMgQVK5cGb1798bNmzcRFhYGPz8/TJ06Fe/fvwcATJs2DcuXL8eJEyfw6tUr/PTTT4WO8WFvb48RI0Zg9OjROHHihGSehw8fBgDY2dmBw+HgzJkziI+PR2pqKkxMTDBz5kz88ssv2L17N0JDQxEQEIANGzZg9+7dAICJEyciODgYs2bNwuvXr7F//354e3uX9CYiROtpNAm5ceMGevbsCRsbG3A4HJw4cULyXk5ODn777Tc0atQIxsbGsLGxwfDhwxEVVfj97QULFkgGPMr7q1evXgmvSelKSs9BalbJDuBEiLYzMjLCjRs3UKNGDfTt2xdOTk4YM2YMMjMzJTUjv/76K4YNG4YRI0bA1dUVJiYm6NOnT6Hz3bJlC/r374+ffvoJ9erVw7hx45CWlgYAqFatGhYuXIjff/8d1tbWmDJlCgBg8eLFmDt3Ljw9PeHk5IRu3brh7NmzcHBwAADUqFEDx44dw4kTJ+Ds7AwvLy8sW7asBLcOIbqBw77uNF+Kzp8/j9u3b8PFxQV9+/bF8ePH4eHhAQBISkpC//79MW7cODg7O+Pz58+YNm0ahEIh/P395c5zwYIFOHr0KK5cuSKZxuPxULmy4u0kkpOTYWZmhqSkJLnVvJqSmSNEvbkXAABhnt9JegU0X3IZH1PFje3odkz5lZmZibCwMDg4OMDAwEDT4WitJ+8TJf9vXN1cY3EUhr5Log72v58FAJyc3AbOtualskxlfkM12iake/fu6N69u8z3zMzMJOMB5Nm4cSNatGiByMhI1KhRQ+58eTweqlSpotZYtcX7z+maDoEQQghRC51qE5KUlAQOhyPpny9PcHAwbGxsULNmTQwZMgSRkZGFls/KykJycrLUHyGEEEJKls4kIZmZmfjtt98wePDgQqt3WrZsCW9vb1y4cAFbtmxBWFgY2rVrh5SUFLmf8fT0hJmZmeTP1ta2JFaBEEIIIfnoRBKSk5ODAQMGgDGGLVu2FFq2e/fu+OGHH9C4cWO4u7vj3LlzSExMlLRul2XOnDlISkqS/L17907dq0AIIYRo3PvP6cjOFWk6DAmtHyckLwGJiIjA1atXlW4oam5ujjp16iAkJERuGYFAQIMKkTJFg+3NiZoo+h0KRQypWbkwM9Qv4YiIrnsU8Qn9ttxF/aqmODdN/vOTSpNW14TkJSDBwcG4cuUKKlWqpPQ8UlNTERoaiqpVq5ZAhNqEo+kAiBbQ1xf/EKWnUwNmXZf3HeZ9p/L84HUHzgsvITKBvnMiHwNw9NEHAMCLaO1p96jRmpDU1FSpGoqwsDA8fvwYFhYWqFq1Kvr374+AgACcOXMGQqEQMTExAMQPkcobubBz587o06ePpL/+zJkz0bNnT9jZ2SEqKgrz588Hl8vF4MGDS38FCSllXC4X5ubmiIuLAyAeSyOvGzf5guV+eXZMZqZ2DfTHGEN6ejri4uJgbm4OLpdbaPmAyEQAwKmgD5jybe1SiJAQ9dFoEuLv749OnTpJXs+YMQMAMGLECCxYsEAyzHGTJk2kPnft2jV07NgRABAaGoqPHz9K3nv//j0GDx6MhIQEWFpaom3btrh3757Kz5IgRNfkdU/PS0TIF4wB2UIR4lOyJNP4Gco/L6Y0mJubl9mhBgjJo9EkpGPHjoXe91Tknmh4eLjU64MHDxY3LEJ0GofDQdWqVWFlZYWcnBxNh6NVDj2IxNabEVLTfH/tqJlgCqGvr19kDQghZYHWN0wlhKiGy+XSD9lXdt3/gA8pQqlpNBopIZqj1Q1TCSGEEFJ2URJCCCk1F55F4+TjD5oOgxCiJeh2DCGkVOQIRZi4NwAA0K62JSyM+RqOiBCiaVQTQghRybtP6fB9GavUoFp50rJySyosQogOoSSkjKChIEhpa7fyGsbs9offm3hNh0Ig7n5MSGG08XeCkhBCSLH4h3/SdAiEkCJ8XWO56PQLXNeCCwhKQgghhJByZuftMIzY+UDTYVASQggpP2gIe0K0CyUhhBBCCNEISkIIIYQQohGUhBBCSh315CCEAJSEEEIIIURDKAnRMXQFSQiRhU4NpCja2CybkhBCCCGEaAQlITqMakUIIYToMkpCCCHlhjZWRxNSGrT1mpWSEEIIIYRoBCUhhBBCCNEISkIIIaWOaW3lMCFllzYedZSE6Bh69AXRVbTvEkK+plISEhsbi2HDhsHGxgY8Hg9cLlfqjxBCCCHaRRuvA3iqfGjkyJGIjIzE3LlzUbVqVXoypRagb4AQQoiuUakm5NatW9i3bx8mTZoEDw8P9O7dW+pPUTdu3EDPnj1hY2MDDoeDEydOSL3PGMO8efNQtWpVGBoaws3NDcHBwUXOd9OmTbC3t4eBgQFatmyJBw8eKLuKZcaFZ9GYcfgxMnOEmg6FEEIIkaJSEmJrawumhpGy0tLS4OzsjE2bNsl8f+XKlVi/fj28vLxw//59GBsbw93dHZmZmXLneejQIcyYMQPz589HQEAAnJ2d4e7ujri4uGLHq4sm7g2AT8AH7LodrulQCNE8qjIk5ZS27voqJSHr1q3D77//jvDw8GItvHv37liyZAn69OlT4D3GGNatW4c///wTvXv3RuPGjfHvv/8iKiqqQI1JfmvWrMG4ceMwatQo1K9fH15eXjAyMsLOnTuLFauui0/J0nQIpJyjEX4JIV9TKQkZOHAg/Pz84OjoCBMTE1hYWEj9qUNYWBhiYmLg5uYmmWZmZoaWLVvi7t27Mj+TnZ2NR48eSX1GT08Pbm5ucj8DAFlZWUhOTpb6I4SUQZQIEaJVVGqYum7dOjWHUVBMTAwAwNraWmq6tbW15L2vffz4EUKhUOZnXr16JXdZnp6eWLhwYTEjJoQoimpFCCld2nrIqZSEjBgxQt1xaNScOXMwY8YMyevk5GTY2tpqMCJCdAdHwbvN1ImOEPI1lZIQABAKhThx4gRevnwJAGjQoAF69eqltnFCqlSpAkA8JknVqlUl02NjY9GkSROZn6lcuTK4XC5iY2OlpsfGxkrmJ4tAIIBAICh+0IQQoiFUu0SKoo0XAiq1CQkJCYGTkxOGDx8OHx8f+Pj4YOjQoWjQoAFCQ0PVEpiDgwOqVKkCX19fybTk5GTcv38frq6uMj/D5/Ph4uIi9RmRSARfX1+5nyGElD5tPBmWdenZuRjgdRf/XFfPOZoQdVApCZk6dSocHR3x7t07BAQEICAgAJGRkXBwcMDUqVMVnk9qaioeP36Mx48fAxA3Rn38+DEiIyPB4XAwffp0LFmyBKdOncLTp08xfPhw2NjYwMPDQzKPzp07Y+PGjZLXM2bMwLZt27B79268fPkSkyZNQlpaGkaNGqXKquoMOqkTTaHnwOiG/fcj8SD8EzzPy28fR0hpU+l2zPXr13Hv3j2pnjCVKlXC8uXL0aZNG4Xn4+/vj06dOkle57XLGDFiBLy9vTF79mykpaVh/PjxSExMRNu2bXHhwgUYGBhIPhMaGoqPHz9KXg8cOBDx8fGYN28eYmJi0KRJE1y4cKFAY1VCSDlUjpN1GrCQaCOVkhCBQICUlJQC01NTU8Hn8xWeT8eOHQsd9IzD4WDRokVYtGiR3DKyxiqZMmUKpkyZonAchBBCCCl9Kt2O+f777zF+/Hjcv38fjDEwxnDv3j1MnDgRvXr1UneMhJAyhhpR6jahiL5Aoh4qJSHr16+Ho6MjXF1dYWBgAAMDA7Rp0wa1atXC33//re4YCSFlgKJdeYl2W37+FRrOv4jwj2maDoWUASrdjjE3N8fJkycRHBwsGQTMyckJtWrVUmtwpCB5V5Bl8cry3ad0PPuQhG4Nq9CTmgnREl7/9a752zcYawc20WwwROepPE4IANSuXRu1a9dWVyyESGm38hoAYOOPTfF9YxsNR0OIdqNeSqQwjGlnbaTCSciMGTOwePFiGBsbS40uKsuaNWuKHRgheR6GfaIkhBBCyiCFk5DAwEDk5ORI/k80L/91D92tIIQQomsUTkKuXbsm8/+EEKIrKFcnRLuo1Dtm9OjRMscJSUtLw+jRo4sdVHn07lM6fj4QiGcfkjQdCiGEEFIqVEpCdu/ejYyMjALTMzIy8O+//xY7qPJo4t5HOB0Uhe833NJ0KISUOGpCSUjp08bGy0r1jklOTpYMTpaSkiI1fLpQKMS5c+dgZWWl9iDLg9D41BKdvzbufIQQQso3pZIQc3NzcDgccDgc1KlTp8D7HA4HCxcuVFtwhBBCFKON3S8JKYpSSci1a9fAGMO3336LY8eOST3Ajs/nw87ODjY21JWSEEIIIUVTKgnp0KEDACAsLAy2trbQ01OpSQkhhBA1o1uupCjaWFum0oipdnZ2AID09HRERkYiOztb6v3GjRsXPzKiVtq48xFCSk9ZfLQDUYZ27gAqJSHx8fEYNWoUzp8/L/N9oVBYrKDKI0VPEPIGJaMkg2g7bbhSp2cQEaJdVLqfMn36dCQmJuL+/fswNDTEhQsXsHv3btSuXRunTp1Sd4xEhzDGsPdeBAIjP2s6FEIIIVpOpZqQq1ev4uTJk2jevDn09PRgZ2eHLl26wNTUFJ6enujRo4e64yQ6wvdlHP488QwAEL6c9oPyQJVaOEb3BkodVQIRbaRSTUhaWppkPJCKFSsiPj4eANCoUSMEBASoLzqic4LjSna8E0IIIWWHSklI3bp18fr1awCAs7Mz/vnnH3z48AFeXl6oWrWqWgMkhBBCSNmk0u2YadOmITo6GgAwf/58dOvWDfv27QOfz4e3t7c64yOEELWh20DqQ9uSqINKScjQoUMl/3dxcUFERARevXqFGjVqoHLlymoLrjyhw5kQUhyUE5CiaGO7IJVuxyxatAjp6emS10ZGRmjWrBmMjY2xaNEitQVHdI827uSEEPWj7s5EHVRKQhYuXIjU1IINENPT09X+7Bh7e3vJ82ry/02ePFlmeW9v7wJl8z9or6yi8wHRJZr6AaMfTkK0i0q3YxhjMg/moKAgqefJqMPDhw+lBj979uwZunTpgh9++EHuZ0xNTSUNZwE68RBSkrRhEDJCiG5SKgmpWLGi1FN08/+4C4VCpKamYuLEiWoN0NLSUur18uXL4ejoKHmOjSwcDgdVqlRRaxyEEPWhRo2EEEDJJGTdunVgjGH06NFYuHAhzMzMJO/x+XzY29vD1dVV7UHmyc7Oxt69ezFjxoxCazdSU1NhZ2cHkUiEZs2aYdmyZWjQoIHc8llZWcjKypK8Tk5OVmvcClHwnEznbkIIIWWFUknIiBEjAAAODg5o3bo19PX1SyQoeU6cOIHExESMHDlSbpm6deti586daNy4MZKSkvDXX3+hdevWeP78OapXry7zM56enmpvy6KsslKlTTe+CCGEKErhhqn5aweaNm2KjIwMJCcny/wrKTt27ED37t1hY2Mjt4yrqyuGDx+OJk2aoEOHDvDx8YGlpSX++ecfuZ+ZM2cOkpKSJH/v3r0rifBLFNWQEEII0TUK14RUrFgR0dHRsLKygrm5uczbIXkNVkviKboRERG4cuUKfHx8lPqcvr4+mjZtipCQELllBAIBBAJBcUMkhBCNoesQUhRtrKlWOAm5evWqpOfLtWvXSiwgeXbt2gUrKyulH44nFArx9OlTfPfddyUUmeaIG/cptluVlds9hBDVUG0p0UYKJyH5e6MU1jOlJIhEIuzatQsjRowAjycd8vDhw1GtWjV4enoCEA+k1qpVK9SqVQuJiYlYtWoVIiIiMHbs2FKNubyi3tCEEEIUpdI4IQDw+fNn7NixAy9fvgQA1K9fH6NGjVL7OCEAcOXKFURGRmL06NEF3ouMjISe3pemLZ8/f8a4ceMQExODihUrwsXFBXfu3EH9+vXVHpc6FfcqhX78CSkaHSaEaBeVkpAbN26gZ8+eMDMzQ/PmzQEA69evx6JFi3D69Gm0b99erUF27dpV7rgCfn5+Uq/Xrl2LtWvXqnX5hBD1ojsDhJQ+bTzuVBq2ffLkyRg4cCDCwsLg4+MDHx8fvH37FoMGDZI7nDohpHQERH5Gp7/8cO1VnKZDIYSQQqmUhISEhODXX38Fl8uVTONyuZgxY0ahvVAIISVvxI4HCPuYhlHeDzUdClGjXKGo0PfpVhMpjLY2TFYpCWnWrJmkLUh+L1++hLOzc7GDIurHoVNUuZGWnavpEIia7b8fiTp/nseNN/Eqz4PajRFtpFKbkKlTp2LatGkICQlBq1atAAD37t3Dpk2bsHz5cjx58kRStnHjxuqJtBy69DwG117HY0Gv+hDwuEV/gBAtpq1XYrrgf8efAgAm7wvA04XuMsto4+bNEYqw7eZbtK1VGY2rm2s6HJm8rodCxBh+6lhL06GUOG3MQ1VKQgYPHgwAmD17tsz3OBxOiQ5cVpaExqdi+flXyBUVPIWM3/MIAOBoaYyx7WqWdmiEKIRq2conRR5CuPdeBFZeeI2VeI3w5cqN8VQaUjJzsPz8KwDAkBZ2MDNS7FEkWblCHPF/j/a1LVGjklFJhljmqZSEhIWFqTuOcmvUroeI/JReaJm4lKxC3yeElA/aWNtRmNcxKZoOoVC5wi9bNLuINjf5bfELxborweBwgDBP7UuulPEo4hNc7NQ/tIaiVEpC7Ozs1B1HuVVUAqIobbkWpatios2oXQRRh3tvEwCUjVuMKy68xuEJrhpbvsJJyKlTp9C9e3fo6+vj1KlThZbt1atXsQMj0i48iwHA4GhZQdOhEFJsZeHkrQnalEPJen6Ypi058wK5IoYFvRpoOhSiIIWTEA8PD8TExMDKygoeHh5yy1E7EPVLz87FxL3i9iHHf2qt4WgIIZpCuZt8aVm52H5L3FTgp46OsDI1UOrz9HwtzVA4CRGJRDL/T0peVs6X7Z2ZQ9teWeuuvEFcShaWejTUyqs3deNwOFTVQLRCaR5uwnz7vKyG/rKUg9OB1lNpnBCiuudRSZh+MBDv1NQWpDS9/5yOkDjtbmgmy7orwdh/PxJvYlM1HQohhGgXDV+vqJSETJ06FevXry8wfePGjZg+fXpxYyrTeqy/hROPoyTdbxWhLde0bVdcg9uaG/iUli23jDZfWWTnUi0SKcOo9osUgkE72/GolIQcO3YMbdq0KTC9devWOHr0aLGDKg9C43T3qlwXa3EIKe8oRyHaSKUkJCEhAWZmZgWmm5qa4uPHj8UOihBCSMlZcOq5QoONlSu0OTRCpSSkVq1auHDhQoHp58+fR82aNLIn0U7lpfV7WfhxiUvORMdV1+B1PVTToZRJ3nfC8TwquRSWpH3V//nRuEaaPy+qNFjZjBkzMGXKFMTHx+Pbb78FAPj6+mL16tVYt26dOuMjX5G3wxR1r0+dO5ru/8QRbbf2yhuEJ6Rj+flXmNjBUdPhlEmZOTSUAtE8lZKQ0aNHIysrC0uXLsXixYsBAPb29tiyZQuGDx+u1gCJtl9LEG1T2l10S+JKKkdIqS4h5YFKSQgATJo0CZMmTUJ8fDwMDQ1RoQKN5EkIIaTsKwN3PLWGyklIbm4u/Pz8EBoaih9//BEAEBUVBVNTU0pIFJSSmaNQOdrfVTP9YCCSMr5sYzpxEPIFHQ5EG6iUhERERKBbt26IjIxEVlYWunTpAhMTE6xYsQJZWVnw8vJSd5xl0jdLryhUTpEfz9JsjFjYsrSlH7pQxHDicZSmwyBErcpCo+OiiEQMp59EoaltRdSoZKTpcEgJU6l3zLRp09C8eXN8/vwZhoaGkul9+vSBr6+v2oIr61Qagl3Lz0Hl4SRJSp52pLK6pagjT5Hrg7NPonE3NEEt8ajq6KP3mHbwMdqvuqbROEjpUKkm5ObNm7hz5w74fL7UdHt7e3z48EEtgZEv5J086OeeEKIu4R/TMHl/gPj/y3toLI57YaolQflPk6pUyCpzPtWSCl+lyLs+fBj+uXQD+YpKNSEikUjmk3Lfv38PExOTYgdFCqGDOz8hBWkmhaZxIb74+kcpJjlTyc9r12VQ/mgUDo12B41TKQnp2rWr1HggHA4HqampmD9/Pr777jt1xYYFCxaAw+FI/dWrV6/Qzxw5cgT16tWDgYEBGjVqhHPnzqktHrUqZOfPzBHi2Yek0oulDCrP55aysO66eKVJCtL09/go4hPaLL+KS89jNBsIkUulJOSvv/7C7du3Ub9+fWRmZuLHH3+U3IpZsWKFWgNs0KABoqOjJX+3bt2SW/bOnTsYPHgwxowZg8DAQHh4eMDDwwPPnj1Ta0wlbeSuB/h+w5f1VCSrL6pBaGldAWpLw9SyIDtXpHVXm0R70ZFX0PAdD/AhMUOpB4aS0qVSmxBbW1sEBQXh0KFDCAoKQmpqKsaMGYMhQ4ZINVRVS4A8HqpUqaJQ2b///hvdunXDrFmzAACLFy/G5cuXsXHjRu3rsVPIb8u9t59KLw6ilZLSc9Bi2RW0qlkJu0e30HQ4pJzKyhViwD/30NTWHAt6NZB6r6QuONR5wZRVBp+cfe5pNPhcPbjVt1bqc9p6fah0TUhOTg4cHR0RHByMIUOGYOXKldi8eTPGjh2r9gQEAIKDg2FjY4OaNWtiyJAhiIyMlFv27t27cHNzk5rm7u6Ou3fvFrqMrKwsJCcnS/3pmhxh2TvY1E2X6hQuPI9GVq4I19/EazqUIlE7C9UwxnA6KArBsSmaDgWAdE3K6kuvkZSegysv4hD0LhHed8KL/LxIxBCdlFFi8ZU0Xah0/JyWjZ/2BWDsv/7ILiMJltJJiL6+PjIzlWvApKqWLVvC29sbFy5cwJYtWxAWFoZ27dohJUX2QRsTEwNra+ns0NraGjExhd8P9PT0hJmZmeTP1tZWbetQGmYeCUJcSlapLU8HjtVyrSx8P7rwg1Bcfm/i8fOBQHRZe0PToRSw4WoI/jz5DLkixX/ophwIgKvnVVzM1/5C29NTba0dkCc1K1fyf1EZOUhUahMyefJkrFixArm5uUUXLobu3bvjhx9+QOPGjeHu7o5z584hMTERhw8fVuty5syZg6SkJMnfu3fv1Dr/4irqQDn66H3pBKIAHTumy7xHEZ91rl3JYf93OKLiPi0U6c66Pldz4/Oi1lzZ3SAwUrmum+eeipOPrTfeKregr2h7YvAo4hPdMlcjldqEPHz4EL6+vrh06RIaNWoEY2Njqfd9fHzUEtzXzM3NUadOHYSEhMh8v0qVKoiNjZWaFhsbW2SbEoFAAIFAoLY4y4IcoQi3gj/Cxb4iTA30NR2O0nTnp6hk9dtyByv6NcLAb2poOhSFzT76RKXP3X+bgGE7HmDu904Y5mqv3qC0REnu1+WxUbkq+Xm/LYXf3i8tOnZtIZdKNSHm5ubo168f3N3dYWNjI3Urw8zMTN0xSqSmpiI0NBRVq1aV+b6rq2uBEVsvX74MV1fXEouprNrgG4xR3g8xbMcDTYeiNrpUI1CcdhZff/JYgPYNIFgSX8XUg4HIFoow9+RzuWXK4e+sXEUdD+r4jnTniCOaolRNiEgkwqpVq/DmzRtkZ2fj22+/xYIFC0qkQSoAzJw5Ez179oSdnR2ioqIwf/58cLlcDB48GAAwfPhwVKtWDZ6engDEw8l36NABq1evRo8ePXDw4EH4+/tj69atJRJfaSnp38638amYsj8QU76the8aiRO8vB+uoHeJSs2rLLZGJ+XD4jMvUKkCHz91rFUqy1Ol5qEkcyh1Jek6leyX0aQ0JikTpoY8GPFVfkZtqVGqJmTp0qX43//+hwoVKqBatWpYv349Jk+eXFKx4f379xg8eDDq1q2LAQMGoFKlSrh37x4sLS0BAJGRkYiOjpaUb926Nfbv34+tW7fC2dkZR48exYkTJ9CwYcMSi7E0sPzXEyVwfP96JAgvopPx074AxeKRE8OeexFYceGVGiMjaqHiPnPxeQxOB5WthwC+ipHdqD0kLgU7boVh5YXXhX4+OTMHuRrsiaY7P+9iZfQ3Xqu9+5SOVp6+aLVM+q6AtuaGSqVJ//77LzZv3owJEyYAAK5cuYIePXpg+/bt0NNT6c5OoQ4ePFjo+35+fgWm/fDDD/jhhx/UHovaKXF0lnQXyNRM9TQwnntCtwaFI/LlCEWY8N8AT21qVYaFMb+IT+i2jOyiE4uYpEy08vRFvSomuDC9fSlEVbp0vU1IcZ8do2uYnJT0VshHAEDyV+f1yy9iFOpqXdqUyhwiIyOlhmV3c3MDh8NBVFTZuloqTxhjCI5LLfXlnn0SjY6rruF5FA1PL5OGT6L5e5mkZZVsLzhVJKRm4Z/roYjP1zW9pJP1yy/Fjd7l1abkl5EtxIVn0Vq17b7uOFRSF8ZaesFdJiibXOW/NbbtZpiao1EPpZKQ3NxcGBgYSE3T19dHTk6OWoMi6icva776Kq6UIxGbvD8A4QnpCt8C0hYZ2UKsufym5J/to0Vncm2sxp20LwCe519hzO6Hmg5Fpt99nmDi3gBMOxio6VAk1l55o+kQtJq8cyQpWUrdjmGMYeTIkVLdWTMzMzFx4kSpbrol1UWXQO1XyPfDNNvfPSO74NOYASA0vvRrZxSx/mowtviFYr1vsEYfd64MTZ9c82rbbMzV14D9wX/77ZP38pPB2ORMbL4WgmGudqhlVfjTvfNfYcalZOJ5VDI61rFU+RbFycfi2uErL0svyS9uslgStzBUmaeqYajyFF1dvmsjbx11bZ2USkJGjBhRYNrQoUPVFgwheTqvvq7pEGR6EVVKQ/oX40yibffDd94Ox+IzL+DmJP9ZF7tuh8HRsgLa17FUeTlfr/eU/QF4GP4Zh/3f4+XibnI/dzzwPcwMv4yF027FNWTlirBuYBN4NK32Zf4qR6Y4kYjhY1oWrEwMii5cwlTt5aKNNWeA+MLGQJ+LampMhknxKZWE7Nq1q6TiKH9K8ECNScpEFTPFTmJa9ntVouRt8vNPoxEan4rJnWrpfOO8ksDAcOzRe3xOz8bYdjWV/vwWP/HggldefhlIMP93cf9tAhaefgEAWNxb+iFpxZFXS5KRI7u2Lc8vh4KkXud1M7/+Jl4qCSkNUw8G4syTaOwa+Q061bMqtOzVV7F4HJlYOoGVAXkXNrpSg1mUsnKqUn+XFqJxWbmFn3SJtEn7AvDXpTfwj1BumGpdocqV6dcnuF+PBGHJ2ZcI/5imnqDy+ZD45aFnhQ00pk0G/HMXrxVooKqsM0/EQw5s9pM9KnR+o739sf5q0eVUpWpCXtwfR039uJZmDc6t4I9w9fSF32vVb9fJvR2jY8kJJSHlnUo7rGJHa2xyJvbei0B6dvF6CKhyMlSlKvljKT4EsCSV5Mk0RYXu3B9Ts4u93ByhCO8+pRd7Psr4eh/Kvxs+CPsE93Xqe/BcalYupuwvupF2af5QFj2iqpbed1GCpmo+h+64j+ikTIzcpVzD6rJYU0tJiA64pmS2rMy5QVa3xp8PBEpdnaqq7+Y7+PPEMyw+86JY81HlZLehhK4QS+scoM7FFDdmbfitGb7jAdqtvIarr2KLLvyf0viuUjJV7xmYP75N10IktSC6Lv/+okq3aU3vbx9TszDH5ymevE/UbCDlBCUhOuBTWvGvJJWhrlEy8xIZTXQD/ts3uMC0kj65ZWQLsfrSazwtpMdGYd7Gp2LyvgC1N34t7noLi7oiVqGBU/6fJkXiu/s2AQCw526E0ssqSerapeIVrIVTZ2JVGj/2JdkzK+hdIlZfeo3MItr8FEbWBc4fx5/iwINI9Np4uzjhEQVRElIGacGFq0Z5XQ/VyHL/9g3Ghqsh6LnxlkqfH77zAc4+jUafzdp18jtwP1LTIShE3RUfJXkcZeUKVWpTUlji8O/dcJUTYG2iaKLVe9NtbLgags1+6j3eg2M1PzzAo4jP6Liq8Jq/snKepyREU9RwxkzNzMVh/3fFn1E+ssbt2HojFKsvfXmmhrJXUKVdvbr8vGaeX/Myung1GO8/i2uOsnJFxbr3q46r5fzV6A+1qMGuMrtSSY+gKl6GakbufCgZS6Q488kvOTNX5QRYVgxFbWt5+6g6D/cj/u+KrCV6U4wGwtraxmLEzgcIT0jHaG9/qenaGW3xaP8j9oi0fEf4rKNBxR4M6etj0GnehQJllp0ruR/1spLNq5s6G/3RNtY+ebeXSkJ0Ugb+PP4MI9vYo11t1cddUYfiJoKzjj6BQ2VjXJvZUW6ZvFs+ant2jBb80qfJacxfFo9lqgnRYcokIPJOBqVxvBV24MSnZOGvi4U/uVRXFHXiuxuagEcRmhmh9tmHJGy8Gqxa9+18CZG6LhwjEtIRmSDu7aKuE2tJX9WWRs2KOvx+7Cl8X8Vh2I4HhZZTpL2GNtQUhJVAt3BZjj16XyrLURd5Fyq6sp/moSSEKE3d56WN11TvyfIiKhmvYkppFNNiSErPweBt99Bvy12NPAr++w238NelN9h6/W2pL1uWsf/6o/2qa0onRZruOfE1df1Iq/OYiknKVEsMjBVeIyf39mMxvyRN/YiuvvymwLbLzBFiyv4AHA/UjgRFt9ILxVASUs6pcvLT5A+BKN+jQNOzc/Hd+pvotu4mcpT4YQ+OTcGsI0HFHndixuHHkpN0Yno2/F7Hyy2bmPGlh1NRvU0A9V6B5v8healCwlbUMzmK86ORniUs9olVJGJ4/C5RMtKpuqiynz/7kIRZR4KKLqiGZRVXrvDLQpPSc6ReK0KRpwmXBlW33YzDj+GxSboReFJGjtT+2HfzHZx5El1gVF2iPtQmRNcocMYuC4MIybLFLxRe10NxbJIralmZIDH9yxgNWbki6HMVy6m7rBUPMnU/7BNuzO6kVAz5N79PwAeMb18T9aqYyuwSXBy+LxUfD0MZZXHX2HgtBGsuF3xCrLpr7BSZ3/cbVG8Yqi6KrvfwnQ8QvrwHQuNT1fusJg4HV17E4nWsdiQp8vgEfCiyzItiNjZXlSLHqdwLFR2rLqGakHJOl+4frrjwCkkZOVh85mWB9xRLvKTLRKphBM6cXPE8kzIKH7RK2R//889iVA1JLUrzybvFXdK2G0XfYrqg4e1ZFE01vXgU8Un9D4tkDGP/9ceqi69xO+Sj0h+XtS2OPXqPvy6+LvQ4V2Y/kne8akETGIXJ3RY6dqFBSQgpV5S5baMMXUrmyoOvv+eJex8pPaiVIudyZb/1yy9isf2mdrTLAYBFMhJ6dYpNVq19ytd+PRKEjddC8EjB7uJFJf3yuvFre02hLiVJiqIkRFNKcGdXaiwFVdqEKFtezeuaNztlY78dkoDaf5xXbzAKKs2TR2EJUUmcZE8/icIY74dILsYQ5oUJifsyeJTM8GWsbu0/ziP9qzFv1N1mRBXj/vXHkrMFf/jLahKryu5W2D6a/xZscYR9VH5AstK6zZ2apfjzmQIjxYOaXXmR7/atju1KlITomLQsekKuLHmnh8Jui8hqN1BcijQyLW3qvpUi9SwQGSe4iIR0+L6Kw6YSel7P+H/9iy6kCO37qpRWmrfJtJGstVd2ixT1vB95bS3+OPFMofkzxuB1PRS3Qz5CJGKYf/KZUoNKrvvqPDX/5DNMPxhYIAliAEZ5P0R4QjrGqusY0QBKQnTMOAV2tg+fMwpclWrLySsrV4jQ+OINi5x3MMq6euxejCebqrKFzgRFYdy//rj8QrvbHJSGz+mqPeOoqCvM/A9TLM7VqKaOgbynSJf2U4CLS9Xtlf9TqlyUl3StYaMFl5TuCQQA+xV8fIHvyzgsP/8KQ7bfx7XXcdh9NwKzjz6RW/7802jcDP7Ss+7rcVF2343AicdRiEhIL3DOSy8DF6XUO0ZTSvBAG77zATgcIMyzR4mHkZSRg8iEdDSqblZIqS8H/KCt9xAYmVjMpYrlir5Ur+f8V9UepeIYCarafiusVJenCu1IP+UrbldPRffh4lZayVqOIj+Y9eddxJ89nMDnyb/mK4v3+gH173vj/vXHsUmucLGzKNZ81HnrkDEmVXuSv8G7Ig8fnbQvAAAQvrzw87WQsQKJYbaMNm66titpdU2Ip6cnvvnmG5iYmMDKygoeHh54/brw0TW9vb3B4XCk/gwMDEopYu1RkncJ8s+7019+6LnxllQmXxh1JSAAcOzRly52198otnxNORGonicTF5cqV7eKfkZWzdQmBQai21FKiZzybZnUdxDJagcivSzF5pOZI0LYx7RCG9mqc4yZ4s5LVAInolG7Hkq9LmwRuSLll6/sGpfWeClfrydToInThD2PSiYYNdLqJOT69euYPHky7t27h8uXLyMnJwddu3ZFWlrhw/iampoiOjpa8hcRoV2P/9YqxTzJ5GX6l54Xb1yL80+jEZWv2l0R8alfaj1UONcUoMiWUPWkvPaK+tujlJZ8FU5KJ7er1DAkvzbXEmiiSVCnv/xQb27BZzypIuhdotz3ihoxtbDPKf8ZhifvExXqwSQrscgRinD2SbTkdWnuM7lChpC4VMw+GoSIhMJ/m2KTM/FbIbdmipI/0Z91VHoAtaVnXxT4vi69KJnxhtRJq2/HXLggfaB5e3vDysoKjx49Qvv27eV+jsPhoEqVKiUdnk6JTEiXVBvO8XmCpIwcbPqxmdqq7op7v13RKkl5NvuF4NDD4j1yXttvWxTmTWwKfjn0GL+41Snw3tc/Cs+jkmDE58GhsrFC85Y1YFNCasEnm5bUiV9b2v6W5A+bOudd3Kc5q5OivX4OPHiH/x1/ihb2FnC0Umy/zG/TtRCsu1L8AQMZmErfxQ9ed/A5PQcPwj5hRGt7ueVmHH6M2yGqPryw8ARj280wtNXwAwtVodU1IV9LSkoCAFhYFH4/MDU1FXZ2drC1tUXv3r3x/PnzQstnZWUhOTlZ6q8sSMrXnc33VRz+ufEWQhHDgQfvcO5pDMITVGsopy1XpvlPcG/j0/AwXHseOV/aftoXgOdRyRj7r3+hJ/6E1Gz0WH8Lnf7yK3R+Rf3wj95deAPp/fcjcb8EnxSbn6K1U8pe1X9durjJUGGfP/G46NE7VfEhMUPqPKBJMUmZuPQ8RurRC3n2PxDXVj8IL/oBj7K2o7I1sW9i5TeOL+x7kvcwvc//bePwhHS5nx/t/RBB75IUjlEV+buz6wqdSUJEIhGmT5+ONm3aoGHDhnLL1a1bFzt37sTJkyexd+9eiEQitG7dGu/fy38AkaenJ8zMzCR/tra2JbEKUrJLYcyC/A03gYID9AhFrEAZRcg6yAo7cNU+Toga51dSV41TDwTKrC0oKUWN2Jrn/ecvt7xUGTQr7/e+sGr8+28T8L/jTzFw6z2l5y+Lur5uLalQkSkzR/o4fBj+GUvPvij2fP++8gbOiy5hxQXZg3OVpjYrrmL8nkfwCSyZhKs0fLvar8gy8sajufoqTqkxQFSx+Ezx95nSpjNJyOTJk/Hs2TMcPHiw0HKurq4YPnw4mjRpgg4dOsDHxweWlpb4559/5H5mzpw5SEpKkvy9e6d4n25tJuukm/+a8d+74dh0LVQty1LXIEKyBMelKj3apaL6br4j+b+8ZahyX/xUUBTmn5JdA6fs7C6/iMXnfK3s07JyERqfilyhCFdexBZIdmS1mJelqMaSygr+7yosQs1dUfMn7DeDCw4DrmjNXLF7x8hYTkkODLjtZhheRBUvST7sL7742uKnnuNcWRn5jinhfzUgRQ/lrmxVq2q3UOQuvZB5KbIPXcn33Cdl9o8coQg/7XsE31dxKsX2pYyWVFUrSKvbhOSZMmUKzpw5gxs3bqB69epKfVZfXx9NmzZFSIj8VvoCgQACgaC4YWodWQdM/kZd/94tXoPdGYceS/7/QclGpcq4E5qA/l5fkoXASPXddsl/klx96Q36NpPev9ZefoPD/u9wcnIbWJkq18sqf61DcYz71x/2lYzgN0v8sL1vV/shNjkL3zeuijNPolFFybjyi0vJhJWJenqPfVagO+LXAtT4XRZF02PlqFJVnpZdslfOmiArqZe+hajNdVbKea9EQr728huceyp/vCFtaRulblpdE8IYw5QpU3D8+HFcvXoVDg4OSs9DKBTi6dOnqFq1aglEqN0SZQweVedP9Q1bXprVqs8+fLkiTPtvOG51J/yyEqm/fYMRnZSJ9VfV+5RcZeVvvxObLK75OPNfb4CY5EzFx8r46gTfYqmvws/jKEpWrgh3Qj8iOlHxsVoU6cKr7YQihj33IvC6iK6a+xQc7KqsK+5v6df7cFqWUK3nAmV/7K+9ll9zsV6JUYQ3a6i2StO0uiZk8uTJ2L9/P06ePAkTExPExIizRDMzMxgaGgIAhg8fjmrVqsHT0xMAsGjRIrRq1Qq1atVCYmIiVq1ahYiICIwdO1Zj66EpadklcwujtJ6hoE1U6QJcmlspLkV++5P8ccj66vptuYOgeV2x5OwL9HOpjlY1K6kUw4fEDPy47b5Kny0NSjd/+mpbyWvwe/TRO8xVcEhvZf3gdRc7RzYvkXkXJS4lC3+qsF6q1DgVZ/Cwu2puAB2sZI3V14+DKKmbIUzBeevWzRgtrwnZsmULkpKS0LFjR1StWlXyd+jQIUmZyMhIREd/6R/++fNnjBs3Dk5OTvjuu++QnJyMO3fuoH79+ppYBVLGKNugeNftMPTccEstyy7qSrs4lp17iSOP3mOQmhqTKkod968VbY/UytNX6XkX1RZJPL6FYj0eVE3eR3tr7rkgKZnqvx0UHJuK9iuvwfv2l0HqIqR66hW+TyiyGVW9TtL26ystD08lWl0ToshB6+fnJ/V67dq1WLt2bQlFpFu0pcZCO6IonrxNeavIRnXSFp4u2Fr9+pt4LDr9Aqv6N0brWpUVntfgbfdwY3YnpZYPFN6TJU/Ep8IHWSqPzj+Lxtmn0fizhxPGtqsps8yP2+6r/Myc8ipv3JkFp19gRGt77FXyNlVWrqhYA37pKi05naudVichpHjK6D4roWvVjnnyhlL+cft9pQZn+5SWjYbzLxZr2fL2iXtvix6fAQCefkiCmaF+sWLIT5Xv0GPTbbUtvzB5t+CWnH2Jz+nZMnuSPf1QsuM+6CJlfiy974QXSNQ/KtC1/ZAST6VVhrZ3LNHy8FSi1bdjiHZS9vH12lIjo4ixu/2RmSMsEPOBByo0KlRwvRljeB6lPT9m2bki9MnXdTm/OT5P0W7lNbUtS5XeMY8VqNlRN3V1ZS9rFsjphq4oWTWFl9Uw1LhQxDDA667SnwuN0/0awf8df6rpEJRCSQhRmqqND3UhGbnyMhZNF12Gq+fVAuNvKPJEzPwUXduDD9+hx3r1tBtRh+tv4ktt6G91PPOHaI73nfAC054Xc2wTdQh8l6jQ6Ktfm7w/oNjL9ldTbzNVyRssTVtREkJKjaI/OJpOVjJyhIhJzsTOfA3ngIIj0BZF0QaLu2WcyEuKIptWSJlBiSirW/VRxGfY/35W02FIkTU0vK57FaP55K4kUBJShmlbxYOiyYUig3yFxKVidzEHWyvK11XwkSo+a0e7FP0dTNyr/Y//1kXadjyqIiu3YG+hfltk37rTJE0PTFcSph18jL33yt4T4SkJKcNC4kquS6cqFD0tKHKydltzvVixqKIsDDb1MZV6chDVacvD8MorZQY/0xWUhJSiop+ZoF6/HSu9BkqKtCoXKXgpqK0t1I+X0AixZeEKmZQPe3TkSvzQw7Lx/K/SoslbsJSElKIh27V3NMmSlLd7K/JjO/5ff7mPyyaEaM7d0ARs0JErcUW7nBOx4j4osThonBCiFuq6mr/0IrbQp0iWNQ/CPuF1rHbdNiNElvmnSmZoeqJ5itZSlwSqCSEq+e7vmwqXzdu/Fd3Py1PvjAH/KD+WASGa8CZW+acAE92gyTMuJSFEJS++GkdCkQGkNJltE0II0T6UhJBSU9gjrwkhhGiGJsdmojYhpMQlZeRggNddlUYwJIQQUrLodkw5EJFQvnt8UAJCSGmh255Ed1ASUkp6bSz45E89iGCETA1EQwgpizx523CDP12rzysCZGMe71+00dOtB62VZZpsrkdJSClJyig40uBR/gK8MBgNK2j2gUe6jAMR+CjtURwZZvIOobteSY37QleyZYnhVwlBA044xnDPgouCQ6AX12DeNdTQi8f3XO3tdTWKewGjeRewj++p5CfVd1xwIIIlEtU2PwD4hvMKO/RXwZZT/KcAK8KeE40p3OMwgToeJ0FddMulZnrigX/cuQ+hj1x01AuUewVjgCw04rzFUt4OXObPwq+8w1+d3Bjqc8LxA9cPZtBcV7queg/R9r8rnJI4yX7tIH8JAgXjMZN3CDN5hxT6zDjuGezRXwYBslEJSeitdwsCZONnrg+89NdCD9IPqtODCNb4cjupo14QpvBOYgv/7yKXpQcR9ugvwzzev5JprnrPMZ57GrIOfH3k4jJ/Njbqr1doXeQZyb2A6/zpqIZ4AJB7ouqs9wgtOS8BAJb4DA+9W9iqvxrmSEE1xKOGUidUhn56N1CfE16s2AHADKmw48So9NlfeEdwgf8bKih5cv6B6wd3vYeoigQc5S9AD717KO7JuZfebbw0GI3R3POSaWcF/8Nc/X0YzL2KZpw36KgXWGCfy6+r3kP48n9FA06Y3DJfYyh82GEHTjQafPU9ddN7gN94B9BX74ZCS5B3ruIjBz9w/VAVCQXea8IJwSDuNQXmL22D/nr48mdCAMUfO+Cq91xqX9SDCL/wjqCt3lNs0N+IhwY/4XfefrhwXmMS9xQ66z2CJ28beurdAcDQjPNGqXPpEcEidOYGYpP+ejTghONv/Y0qJiQMK3hb8TvvQKGlLvB/x0z9I1ig7y01nY8ccCBCRSTDTe+RQudhTdaEUMNUDdCDCO31giSvXfTewI4Ti7G887ghbIThOXOkyhshEy8MRktNq633AQLkYFnuEIzhnsVc/X2S91bpb4V95j7U5bzDfN6/SIMhxuXMAAqcmFiBaZWQhERUgBBcdNN7gAqcDBwVdoAZUpECI4igBy6EqIwkxMJC6rOW+Iyt/LUAgM5Zq3CW/z9sF36Hv3IHSspYIBnjeWewX9gZkcxayS3H4MiJwltWFey//Lml3isAwBTeSQDAvlw3RKNSoXP5Q38/AKCf6CbGcM/BUS8a23LDMY53DgDQXvgEfiJnNOBEIJhVw2b9dXDjBmJ49m+4IXJGZY5iT8cFgFZ6L9CO+wzt8AyLcoejk14gdvFXAQB6cu/ipqgx6nLeoTM3EH2yFmIA1w+19T6gNj5gSs5Umdug4PcoZohMZMAAALBAX5z0zNHfj0vCb7CevxGfWQW8YdWxJGcolutvwy5hN/yl/w8AoFmmFx4aTJbMK4EdxGCe+MfCKXMn3PQC8CvvCCblTEd1TjwW6nvjovAbXBE1w21RIwDAMt52/PjfZ2pm7oUIHBmxyo/fEp+xTH8n9gjd8C9/BQCgbdY6vGdWhWxhMT2IIPpvn5jGOw4AGM29gPXCvuirdwNr+F4YlP0n7onqAwCqc+IwnHsZu3K7IRqV0IQTglX6WwEA14WN0VzvDZrz32ATgL9yfsBGYR/JsmpyotCY8xZXRM2QCiMAgCnSMIl3CieEbfCa1ZCUXc/fBACYp78HO4XdpWJeor9L8v/FOUOwQ9hD8iObBb7kvbxjait/DdpkbShyWwBfkpBv9QLwO+8AZuRMwjNWE4A4Ib0m+BWA+Hv/BFMIkA0v/jrJ52OzK0q+V1m26q9BV+4jHMjthAqcDEzLmSLZ/pO4p/CL/jEk84zQOGu71OdOCOZJve6gF4Rueg9wTNgO/qye3LXpyb0HAGin9xRXRC5Frr8NPuIAfykAwFfYFBty+6AmJ0qyb+SZyDuDibwzUtMG4xrSswXYwV+NBGYCl6x/5C6nm94DTOUdx885UyTTqnE+4qzgfwCAOpx36J69QvKeBZLhpBeBe6L6EIIrc57ueg8xkOcHAFieO1jOkhkMOOIa4LxzIABUQDqeGYxFAjOBMTJhwMnBspzB8BfVBQAEsDoQIFtq/xLPTXMoCdGAJbyd+JF3VfLag3sH6UwAAGjPfYpf2WGEimxwQtQWg7m+8NTfIXM+znrip7zmT0DyLODtxkjeJclro5wspEOAvB+A2pz3uCyYjQ+sErpnLUdTvRC46z2Q/Ijk103vAdy4gXgkqo1+2QtxkL8Y3+i9we7cLmiiF4qFOcPRg3sfY3hfrvZ8BbMAiJOD/EnIMf58OOjFSg781Tn9sUHYV8baSf9YNeCE4azgD/G8hU0xJmeWzG1SlZOAaFYJtTnvYYgsPGGOAAArfIajXhTuihpIyi7Lt13zEhAAGMS9Bm/+SgCAn9AZHbnihHE09wJuiJwhYl/iEv/wC/A77yDCmTUOCr+ViscMXxokmyJNkoAAQCO9cDTSC5e8Pi6YL3OdrPEJP/FOYgTvMgDgnLAFfsqZLlVmDm8fJvDOYnnOIHgJe+WLLxvr+RsBABU5qWjJeYXTgj8BAH/pfTm57uD/JTW/tnpfRsd8mS8BPi/4kiCP4l3EKFzE9tzu2JjrIbXvXOf/gmBWDWNyZqIGJw51Oe+wUH83EpkxBmXPRRIqwJHzAVyI8IFVxgjuRUzinYYJJwNduF+e4juDdxS/5YzHHN5+nBK2hh5ECGC14ar3Ag044dgu/A7hBkMAAE0y/0EiTL58Vv8oBvD8UJ0jfmbTQf4SHBO2hT6EaKH3ClU4nzGedxa1M/+V+nHswH0itS1m6h+RSkKuCmZ+2W653bE4dyg26q9He+5TTOKdRt1Mb3TUC8ItUUOp+QzgXsNJYRvIMld/H84JW+Guwc/51qUC8h8DFSDr6dIMemCYxvNBuOhLUs8YBxWQjp3/fa/b+GvQLmsdVuhvQz/ul4EGa3Di8ImZgo9cqbnW47zDbXydhDAs5u3Ca2aLrv99R3mJagyzwLLcH8Gghw7/HS+mnKJronb/l2wO5l1D+6y1sMLnAsnIEt5Oyf/rcN4jkmOFqbzj+Du3LxpywhDKbGDDScBI3kU8F9njpLA1jDhZks905gaiMzcQd4T1i4wnj7uePwCgEufLaMYd9ILQiPMWh4Qd4agXjaciB0nitkZ/i6Rc/s846YmfYdOQ8xZOepGSRBcAXojs4C3sisPCTv9NYeik9xj/5EsGZcl/LgQgqUXjQIRnBmMLxPA//S81Kltye2IS7zSGZIuP4/Hcs5iZMwGng6Lwjb30RWVp4TBNdhDWUsnJyTAzM0NSUhJMTU3VMk/7388CAKohHrcNpin0mUU5wzBPf0+hZXyEbdGXe6vIeV0RNkUdznvsFrqjG/cBvtF7o1AM6tAycyNiYQFHzgdJcpLfvtzOOCdqgaqcT6jDeY/xPPG2apy5DUO5l2HKSS9wteKSuQVTeCcwinexwPz6Zc3HMcFCAOIrvZ95xyXl7omc0Ervpcrrsi63L0ZwL6EiR3417fDs3/BU5IB2ek8lV8KqqJ35L4yQiSCD8QXe65S1GuHMGjU50TjL/5/kqggAtub2kGxDTduf+61Uwp1nV667zO9OEUtyhuBPGYn3spzB2Cr8XpKUqNOU7J/xitkiilUuUCt5MLcjBv135QoAR3Lb4wfeDVwTOqMTN0iqbDbjgs9R7DblXWF9DM75E+EGPxZ4zy1rJaJZJZzh/w8OegWr/KOZBT6wymiuwHH+WFQTr0Q1pNYhzz2RE37M/gP6yMUg7jUs1N9dyHwcsSp3gFRbj2HZvyNI5IhkGGGb/mp04QYUGY9b1kokMhPs5K+EBSdFkkQq46iwPfpzFbmtVLT9uZ1gxMmCB/eO3DKRIkvU0IuX+V6PrGWSmhFZopgFHorqobeM+dtn7gPAQX/udYSIquE1qy51UZBnUPafWKe/CVU4qrUvPC1shZ6LVTseZVHmN5SSEBlKKgmZzTuIn3in1DI/XbMyZwBm6x8u9eXOzJkgueVACCElIZPpS10I5JfDuNBXMPHUlERmDPOFUWqbnzK/odQwtZT00btZbhMQABpJQABQAkIIKXHyEhAAWp+AAIA5R3PjWFESUkrW8rcUXYgQQggpR3QiCdm0aRPs7e1hYGCAli1b4sGDB4WWP3LkCOrVqwcDAwM0atQI586dK7Q8IYQQQkqf1ichhw4dwowZMzB//nwEBATA2dkZ7u7uiIuT/TC0O3fuYPDgwRgzZgwCAwPh4eEBDw8PPHv2TGZ5QgghhGiG1jdMbdmyJb755hts3CjuZigSiWBra4uff/4Zv//+e4HyAwcORFpaGs6c+dKbolWrVmjSpAm8vLwUWmZJNEzFAjP1zIcQQghRtwWKj39UlDLTMDU7OxuPHj2Cm5ubZJqenh7c3Nxw967sYYnv3r0rVR4A3N3d5ZYHgKysLCQnJ0v9EUIIIaRkaXUS8vHjRwiFQlhbS4+saW1tjZgY2UM6x8TEKFUeADw9PWFmZib5s7W1LX7whBBCCCkUjZgKYM6cOZgxY4bkdXJysvoTkV4bgVP/De377Z9A4D7gcxgw6S4gqCCebmYLcDhAchTwcDtQqwtgXR8QCYH4V+LpiRFAlcaA/07g9TmglhvgOhmoXAfQNwKS3gHxr4EGfYDIu0CN1sC7+0ClWoC+IfBXHSA3Axh1AWBCwLsHYNMMGHsFeHkKODKyYOzNRgBcfUBgCnT4DVj6X5I3+iJQzQXQ4wHZqcCbi+I4PocD0UHiaabVAPu24s9z+UBWCuAzHnD9CRCYAXf+BmKeAk69gDcXAKGMZ0MM9QGsGwLCLCAnAzC0AAxMgeQPgEVNQJgjnv7iJGDhANi1AQL3AKd+BvrtAKo6A8aWgIEZkJ4ArBKPoopGA8TfhR4PqGAN6HHFsSeEABmfxduxjjuwo4u4fK0u4uWYVQfq9wZqtALCbwG1uwIfXwOZyUDYdaD5GPH8UqIAk6pAxB3gynzxd+DhBSyqKJ7fqAvi5XE44phfnBCvfxVn4NZaIOIW0H2VeF2yU8Xff+5/z+tw9wQu/jd6qUVNwKE94LZQ/B2nJ3yJc2kVgP33XJIui4B634v3h3o9gOsrgbsbpbe1hSMw4hTw7BjgMlL8fZ2cDLz1A+p0B/p4AS9PA9lp4u2ZEAx8egs8/2847AVJ4v01NRY4OQUwrgx8v1a8b978C7BuBNi2AHZ0BZoMBlx/Bm7/DVxbAvTfCTTsV/DW5Xd/ifez2OdA7S7Avv7ifQYAzGoAvTcCz44C7X4VH0PJUeL9I+OzeN/Y2PzLvOa8B1JixOtjVl38HRr+930IcwEuD0j/BLw6A9R2F89DlANE3hPH2Ww40GG2eJ1DfIHGA4ArCwH/HcD0Z8D+AUDcC6DXBnHZ4MvieMdcFu8rptXE3+Grs0CVhsDN1UD1bwBjK/Ex02Uh0Kg/cG4W8Po84PituLxlPXHMYdeBmh2Bb+cCx8YC9m0AczvgmniIckzxF8caHSSOw3kQ0GSo+PvIShZ/n/v6i9cLAGaFAp8jgJRo8bHz4iRw/csw4xLWDYHY/9rVTbghfu3nCYTdAAYdAA4PB6ICgR8PAhmJwOFh4rKOnYGYJwDfWLyv6xsDM56LP3d1ifg4snICXl8AMj4BHD3g4xtx2SqNxZ9tP0t8fFg4AEaVxOeRjETxfr3mv9FVf9gNVHIUf5cpMeJzWuxT4GOw+Njw/l58jDYdCgTuBTy2iM8jBwaK9y0uX3y+7PQHUKWReHkPtoqPR6PK4nPIzq5ARQdgykPxMcnli4+JD/7i7/1r/XeK1yfyvng9I+8ANVyBas0BHl98vri5WnycCUzE+1fMU3EMAhPx+ln/N8rr0dHiY/LnAPF2PjZGvM4V7YAPj8T7qnFlIOm9eNtwOOJzgZkt8P6BeP/S4wJvr385bwBA323i8269HgXjLy1Mi2VlZTEul8uOHz8uNX348OGsV69eMj9ja2vL1q5dKzVt3rx5rHHjxgovNykpiQFgSUlJyoZcerJSGXt1nrHsDOU+l5PFmDBX/vvpnxn7HMHYfFPxX25OwTLv/Bl7fVG55RZGJBL/m5XKWOxLxj6FMXZ+DmOJ79S3jPw+RzB2dzNjmSmKlU9LYOzZcfG2U4e/mzC2yJKxrLTizUeReCLuMuZZg7HAfbLff3Hqy3ddHLEvGUuJK9488uRkMfbyrHhflCUtgbEnRxjLTldsfjHPCt+f1U2ZZSR9+LL/F0dOpvLnAnmEQsZOTWXs4Y4v2+3Aj4xlJCl+TJ7/nbH1LoxlJotfi0SMRT9RPEZFt0l2OmOfIxUrm6ew819hcjILjytvWxX3WCppn8IYe3pU/D2XEGV+Q3WiYWqLFi2wYYP4wU0ikQg1atTAlClT5DZMTU9Px+nTpyXTWrdujcaNG2u2YaquufGX+Eq3xThNR1L2CHPFV9f6hqWzPMbEV0ay5GYDO9zEV44915VOPKUt5ing1Vb8//mJ8rcFKSivVqpBH+AHb42GovX+biKu3QbU2shTFynzG6r1t2NmzJiBESNGoHnz5mjRogXWrVuHtLQ0jBo1CgAwfPhwVKtWDZ6e4ucVTJs2DR06dMDq1avRo0cPHDx4EP7+/ti6dWthiyFfaz+z6DJENVye+K+0FPajy+OLq9fLMnO7L/+nBEQ53VcC9/8BuizWdCTa78dDwKU/gQ4FL46JfFqfhAwcOBDx8fGYN28eYmJi0KRJE1y4cEHS+DQyMhJ6el/a17Zu3Rr79+/Hn3/+if/973+oXbs2Tpw4gYYNG8pbBCGkLDMwBWa8AngCTUeie1pOEP+RolnWBYYc0XQUOkfrb8doAt2OIYQQQlRTZsYJIYQQQkjZRUkIIYQQQjSCkhBCCCGEaAQlIYQQQgjRCEpCCCGEEKIRlIQQQgghRCMoCSGEEEKIRmj9YGWakDd0SnJysoYjIYQQQnRL3m+nIsOQURIiQ0pKCgCo/0m6hBBCSDmRkpICMzOzQsvQiKkyiEQiREVFwcTEBBw1PWsiOTkZtra2ePfuXZkYhZXWR7vR+mivsrQuAK2PttPE+jDGkJKSAhsbG6nHqshCNSEy6OnpoXr16iUyb1NT0zKxY+eh9dFutD7aqyytC0Dro+1Ke32KqgHJQw1TCSGEEKIRlIQQQgghRCMoCSklAoEA8+fPh0BQNh4nTuuj3Wh9tFdZWheA1kfbafv6UMNUQgghhGgE1YQQQgghRCMoCSGEEEKIRlASQgghhBCNoCSEEEIIIRpBSUgp2bRpE+zt7WFgYICWLVviwYMHmg4Jnp6e+Oabb2BiYgIrKyt4eHjg9evXUmUyMzMxefJkVKpUCRUqVEC/fv0QGxsrVSYyMhI9evSAkZERrKysMGvWLOTm5kqV8fPzQ7NmzSAQCFCrVi14e3uX6LotX74cHA4H06dP19l1+fDhA4YOHYpKlSrB0NAQjRo1gr+/v+R9xhjmzZuHqlWrwtDQEG5ubggODpaax6dPnzBkyBCYmprC3NwcY8aMQWpqqlSZJ0+eoF27djAwMICtrS1Wrlyp9nURCoWYO3cuHBwcYGhoCEdHRyxevFjq2RLavD43btxAz549YWNjAw6HgxMnTki9X5qxHzlyBPXq1YOBgQEaNWqEc+fOqXV9cnJy8Ntvv6FRo0YwNjaGjY0Nhg8fjqioKJ1cn69NnDgRHA4H69at0+n1efnyJXr16gUzMzMYGxvjm2++QWRkpOR9nTnfMVLiDh48yPh8Ptu5cyd7/vw5GzduHDM3N2exsbEajcvd3Z3t2rWLPXv2jD1+/Jh99913rEaNGiw1NVVSZuLEiczW1pb5+voyf39/1qpVK9a6dWvJ+7m5uaxhw4bMzc2NBQYGsnPnzrHKlSuzOXPmSMq8ffuWGRkZsRkzZrAXL16wDRs2MC6Xyy5cuFAi6/XgwQNmb2/PGjduzKZNm6aT6/Lp0ydmZ2fHRo4cye7fv8/evn3LLl68yEJCQiRlli9fzszMzNiJEydYUFAQ69WrF3NwcGAZGRmSMt26dWPOzs7s3r177ObNm6xWrVps8ODBkveTkpKYtbU1GzJkCHv27Bk7cOAAMzQ0ZP/8849a12fp0qWsUqVK7MyZMywsLIwdOXKEVahQgf399986sT7nzp1jf/zxB/Px8WEA2PHjx6XeL63Yb9++zbhcLlu5ciV78eIF+/PPP5m+vj57+vSp2tYnMTGRubm5sUOHDrFXr16xu3fvshYtWjAXFxepeejK+uTn4+PDnJ2dmY2NDVu7dq3Ork9ISAizsLBgs2bNYgEBASwkJISdPHlS6jdFV853lISUghYtWrDJkydLXguFQmZjY8M8PT01GFVBcXFxDAC7fv06Y0x8MtLX12dHjhyRlHn58iUDwO7evcsYEx8senp6LCYmRlJmy5YtzNTUlGVlZTHGGJs9ezZr0KCB1LIGDhzI3N3d1b4OKSkprHbt2uzy5cusQ4cOkiRE19blt99+Y23btpX7vkgkYlWqVGGrVq2STEtMTGQCgYAdOHCAMcbYixcvGAD28OFDSZnz588zDofDPnz4wBhjbPPmzaxixYqS9ctbdt26ddW6Pj169GCjR4+Wmta3b182ZMgQnVufr38USjP2AQMGsB49ekjF07JlSzZhwgS1rY8sDx48YABYRESEzq7P+/fvWbVq1dizZ8+YnZ2dVBKia+szcOBANnToULmf0aXzHd2OKWHZ2dl49OgR3NzcJNP09PTg5uaGu3fvajCygpKSkgAAFhYWAIBHjx4hJydHKvZ69eqhRo0aktjv3r2LRo0awdraWlLG3d0dycnJeP78uaRM/nnklSmJ9Z88eTJ69OhRYHm6ti6nTp1C8+bN8cMPP8DKygpNmzbFtm3bJO+HhYUhJiZGKhYzMzO0bNlSan3Mzc3RvHlzSRk3Nzfo6enh/v37kjLt27cHn8+XWp/Xr1/j8+fPaluf1q1bw9fXF2/evAEABAUF4datW+jevbtOrk9+pRl7aR5L+SUlJYHD4cDc3Fwn10ckEmHYsGGYNWsWGjRoUOB9XVofkUiEs2fPok6dOnB3d4eVlRVatmwpdctGl853lISUsI8fP0IoFEp90QBgbW2NmJgYDUVVkEgkwvTp09GmTRs0bNgQABATEwM+ny858eTJH3tMTIzMdct7r7AyycnJyMjIUNs6HDx4EAEBAfD09Czwnq6ty9u3b7FlyxbUrl0bFy9exKRJkzB16lTs3r1bKp7C9quYmBhYWVlJvc/j8WBhYaHUOqvD77//jkGDBqFevXrQ19dH06ZNMX36dAwZMkQn1ye/0oxdXpmSPJdkZmbit99+w+DBgyUPQNO19VmxYgV4PB6mTp0q831dWp+4uDikpqZi+fLl6NatGy5duoQ+ffqgb9++uH79uiQOXTnf0VN0CQBxDcKzZ89w69YtTYeiknfv3mHatGm4fPkyDAwMNB1OsYlEIjRv3hzLli0DADRt2hTPnj2Dl5cXRowYoeHolHf48GHs27cP+/fvR4MGDfD48WNMnz4dNjY2Ork+5UVOTg4GDBgAxhi2bNmi6XBU8ujRI/z9998ICAgAh8PRdDjFJhKJAAC9e/fGL7/8AgBo0qQJ7ty5Ay8vL3To0EGT4SmNakJKWOXKlcHlcgu0So6NjUWVKlU0FJW0KVOm4MyZM7h27RqqV68umV6lShVkZ2cjMTFRqnz+2KtUqSJz3fLeK6yMqakpDA0N1bIOjx49QlxcHJo1awYejwcej4fr169j/fr14PF4sLa21pl1AYCqVauifv36UtOcnJwkrd/z4ilsv6pSpQri4uKk3s/NzcWnT5+UWmd1mDVrlqQ2pFGjRhg2bBh++eUXSa2Vrq1PfqUZu7wyJbFueQlIREQELl++LPUYeF1an5s3byIuLg41atSQnBsiIiLw66+/wt7eXufWp3LlyuDxeEWeH3TlfEdJSAnj8/lwcXGBr6+vZJpIJIKvry9cXV01GJm4W+GUKVNw/PhxXL16FQ4ODlLvu7i4QF9fXyr2169fIzIyUhK7q6srnj59KnUA552w8g4SV1dXqXnklVHn+nfu3BlPnz7F48ePJX/NmzfHkCFDJP/XlXUBgDZt2hToLv3mzRvY2dkBABwcHFClShWpWJKTk3H//n2p9UlMTMSjR48kZa5evQqRSISWLVtKyty4cQM5OTlS61O3bl1UrFhRbeuTnp4OPT3p0w2Xy5Vc1ena+uRXmrGX1v6Xl4AEBwfjypUrqFSpktT7urQ+w4YNw5MnT6TODTY2Npg1axYuXryoc+vD5/PxzTffFHp+0KVzN/WOKQUHDx5kAoGAeXt7sxcvXrDx48czc3NzqVbJmjBp0iRmZmbG/Pz8WHR0tOQvPT1dUmbixImsRo0a7OrVq8zf35+5uroyV1dXyft53by6du3KHj9+zC5cuMAsLS1ldvOaNWsWe/nyJdu0aVOJdtHNk793jK6ty4MHDxiPx2NLly5lwcHBbN++fczIyIjt3btXUmb58uXM3NycnTx5kj158oT17t1bZrfQpk2bsvv377Nbt26x2rVrS3U7TExMZNbW1mzYsGHs2bNn7ODBg8zIyEjtXXRHjBjBqlWrJumi6+PjwypXrsxmz56tE+uTkpLCAgMDWWBgIAPA1qxZwwIDAyW9RUor9tu3bzMej8f++usv9vLlSzZ//nyVuoAWtj7Z2dmsV69erHr16uzx48dS54b8PUN0ZX1k+bp3jK6tj4+PD9PX12dbt25lwcHBkq6zN2/elMxDV853lISUkg0bNrAaNWowPp/PWrRowe7du6fpkBgAmX+7du2SlMnIyGA//fQTq1ixIjMyMmJ9+vRh0dHRUvMJDw9n3bt3Z4aGhqxy5crs119/ZTk5OVJlrl27xpo0acL4fD6rWbOm1DJKytdJiK6ty+nTp1nDhg2ZQCBg9erVY1u3bpV6XyQSsblz5zJra2smEAhY586d2evXr6XKJCQksMGDB7MKFSowU1NTNmrUKJaSkiJVJigoiLVt25YJBAJWrVo1tnz5crWvS3JyMps2bRqrUaMGMzAwYDVr1mR//PGH1I+aNq/PtWvXZB4rI0aMKPXYDx8+zOrUqcP4fD5r0KABO3v2rFrXJywsTO654dq1azq3PrLISkJ0bX127NjBatWqxQwMDJizszM7ceKE1Dx05XzHYSzfkIWEEEIIIaWE2oQQQgghRCMoCSGEEEKIRlASQgghhBCNoCSEEEIIIRpBSQghhBBCNIKSEEIIIYRoBCUhhBBCCNEISkIIIYQQohGUhBBCtBaHw8GJEyc0HQYWLFiAJk2aaDoMQsocSkIIKcfi4+MxadIk1KhRAwKBAFWqVIG7uztu376t6dDUIjw8HBwOB48fP9Z0KIQQGXiaDoAQojn9+vVDdnY2du/ejZo1ayI2Nha+vr5ISEjQdGiEkHKAakIIKacSExNx8+ZNrFixAp06dYKdnR1atGiBOXPmoFevXpJya9asQaNGjWBsbAxbW1v89NNPSE1Nlbzv7e0Nc3NznDlzBnXr1oWRkRH69++P9PR07N69G/b29qhYsSKmTp0KoVAo+Zy9vT0WL16MwYMHw9jYGNWqVcOmTZsKjfndu3cYMGAAzM3NYWFhgd69eyM8PFzhdfbz8wOHw4Gvry+aN28OIyMjtG7dusBj0ZcvXw5ra2uYmJhgzJgxyMzMLDCv7du3w8nJCQYGBqhXrx42b94seW/06NFo3LgxsrKyAADZ2dlo2rQphg8frnCshJQLan0cHiFEZ+Tk5LAKFSqw6dOns8zMTLnl1q5dy65evcrCwsKYr68vq1u3Lps0aZLk/V27djF9fX3WpUsXFhAQwK5fv84qVarEunbtygYMGMCeP3/OTp8+zfh8Pjt48KDkc3Z2dszExIR5enqy169fs/Xr1zMul8suXbokKQOAHT9+nDHGWHZ2NnNycmKjR49mT548YS9evGA//vgjq1u3rtTTePPLeyJsYGAgY+zL00lbtmzJ/Pz82PPnz1m7du1Y69atJZ85dOgQEwgEbPv27ezVq1fsjz/+YCYmJszZ2VlSZu/evaxq1ars2LFj7O3bt+zYsWPMwsKCeXt7M8bEj2KvWbMmmz59OmOMsZkzZzJ7e3uWlJSk2JdDSDlBSQgh5djRo0dZxYoVmYGBAWvdujWbM2cOCwoKKvQzR44cYZUqVZK83rVrFwPAQkJCJNMmTJjAjIyMpB6F7u7uziZMmCB5bWdnx7p16yY174EDB7Lu3btLXudPQvbs2cPq1q3LRCKR5P2srCxmaGjILl68KDNWeUnIlStXJGXOnj3LALCMjAzGGGOurq7sp59+kppPy5YtpZIQR0dHtn//fqkyixcvZq6urpLXd+7cYfr6+mzu3LmMx+OxmzdvyoyRkPKMbscQUo7169cPUVFROHXqFLp16wY/Pz80a9YM3t7ekjJXrlxB586dUa1aNZiYmGDYsGFISEhAenq6pIyRkREcHR0lr62trWFvb48KFSpITYuLi5Navqura4HXL1++lBlrUFAQQkJCYGJiggoVKqBChQqwsLBAZmYmQkNDlVrvxo0bS/5ftWpVAJDE9vLlS7Rs2VJunGlpaQgNDcWYMWMkcVSoUAFLliyRisPV1RUzZ87E4sWL8euvv6Jt27ZKxUhIeUANUwkp5wwMDNClSxd06dIFc+fOxdixYzF//nyMHDkS4eHh+P777zFp0iQsXboUFhYWuHXrFsaMGYPs7GwYGRkBAPT19aXmyeFwZE4TiUQqx5mamgoXFxfs27evwHuWlpZKzSt/bBwOBwAUji2vPcy2bdsKJCtcLlfyf5FIhNu3b4PL5SIkJESp+AgpL6gmhBAipX79+khLSwMAPHr0CCKRCKtXr0arVq1Qp04dREVFqW1Z9+7dK/DayclJZtlmzZohODgYVlZWqFWrltSfmZmZ2mJycnLC/fv35cZpbW0NGxsbvH37tkAcDg4OknKrVq3Cq1evcP36dVy4cAG7du1SW4yElBWUhBBSTiUkJODbb7/F3r178eTJE4SFheHIkSNYuXIlevfuDQCoVasWcnJysGHDBrx9+xZ79uyBl5eX2mK4ffs2Vq5ciTdv3mDTpk04cuQIpk2bJrPskCFDULlyZfTu3Rs3b95EWFgY/Pz8MHXqVLx//15tMU2bNg07d+7Erl278ObNG8yfPx/Pnz+XKrNw4UJ4enpi/fr1ePPmDZ4+fYpdu3ZhzZo1AIDAwEDMmzcP27dvR5s2bbBmzRpMmzYNb9++VVuchJQFlIQQUk5VqFABLVu2xNq1a9G+fXs0bNgQc+fOxbhx47Bx40YAgLOzM9asWYMVK1agYcOG2LdvHzw9PdUWw6+//gp/f380bdoUS5YswZo1a+Du7i6zrJGREW7cuIEaNWqgb9++cHJyknSfNTU1VVtMAwcOxNy5czF79my4uLggIiICkyZNkiozduxYbN++Hbt27UKjRo3QoUMHeHt7w8HBAZmZmRg6dChGjhyJnj17AgDGjx+PTp06YdiwYVLdlAkp7ziMMabpIAgh5Y+9vT2mT5+O6dOnazoUQoiGUE0IIYQQQjSCkhBCCCGEaATdjiGEEEKIRlBNCCGEEEI0gpIQQgghhGgEJSGEEEII0QhKQgghhBCiEZSEEEIIIUQjKAkhhBBCiEZQEkIIIYQQjaAkhBBCCCEa8X+63WQuHKVg8gAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Lightgbm"
      ],
      "metadata": {
        "id": "yZWVQoCm0PRB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import lightgbm as lgb\n",
        "\n",
        "final_model = lgb.LGBMRegressor(\n",
        "    boosting_type='gbdt',\n",
        "    objective='regression',\n",
        "    num_leaves=31,\n",
        "    learning_rate=0.05,\n",
        "    n_estimators=100\n",
        ")\n",
        "final_model.fit(X_train_scaled, y_train_scaled.ravel())\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 181
        },
        "id": "od9jXc9k0Ogw",
        "outputId": "32e71d89-0274-4456-a28f-3854e3562a8e"
      },
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001522 seconds.\n",
            "You can set `force_col_wise=true` to remove the overhead.\n",
            "[LightGBM] [Info] Total Bins 19501\n",
            "[LightGBM] [Info] Number of data points in the train set: 1811, number of used features: 80\n",
            "[LightGBM] [Info] Start training from score -0.000000\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LGBMRegressor(learning_rate=0.05, objective='regression')"
            ],
            "text/html": [
              "<style>#sk-container-id-20 {color: black;}#sk-container-id-20 pre{padding: 0;}#sk-container-id-20 div.sk-toggleable {background-color: white;}#sk-container-id-20 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-20 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-20 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-20 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-20 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-20 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-20 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-20 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-20 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-20 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-20 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-20 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-20 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-20 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-20 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-20 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-20 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-20 div.sk-item {position: relative;z-index: 1;}#sk-container-id-20 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-20 div.sk-item::before, #sk-container-id-20 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-20 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-20 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-20 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-20 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-20 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-20 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-20 div.sk-label-container {text-align: center;}#sk-container-id-20 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-20 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-20\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LGBMRegressor(learning_rate=0.05, objective=&#x27;regression&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-23\" type=\"checkbox\" checked><label for=\"sk-estimator-id-23\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LGBMRegressor</label><div class=\"sk-toggleable__content\"><pre>LGBMRegressor(learning_rate=0.05, objective=&#x27;regression&#x27;)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "evaluate_model(final_model, X_train_scaled, X_test_scaled, y_train, y_test, scaler_y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 704
        },
        "id": "iaD1495T2d2f",
        "outputId": "85f3ac53-7e52-4b6e-fd23-8cacedca19b4"
      },
      "execution_count": 72,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training MSE: 0.11, Training MAE: 0.12\n",
            "Testing MSE: 0.36, Testing MAE: 0.25\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        " Feedforward Neural Network"
      ],
      "metadata": {
        "id": "inOG6RTE0toh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.neural_network import MLPRegressor\n",
        "\n",
        "final_model = MLPRegressor(\n",
        "    hidden_layer_sizes=(1000,),   # Single hidden layer with 100 neurons\n",
        "    activation='relu',\n",
        "    solver='adam',\n",
        "    learning_rate='adaptive',\n",
        "    max_iter=500\n",
        ")\n",
        "final_model.fit(X_train_scaled, y_train_scaled.ravel())\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "vYs6-pJt0tYk",
        "outputId": "8ded5be0-ac84-4960-a310-df8e6870a159"
      },
      "execution_count": 73,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "MLPRegressor(hidden_layer_sizes=(1000,), learning_rate='adaptive',\n",
              "             max_iter=5000)"
            ],
            "text/html": [
              "<style>#sk-container-id-21 {color: black;}#sk-container-id-21 pre{padding: 0;}#sk-container-id-21 div.sk-toggleable {background-color: white;}#sk-container-id-21 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-21 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-21 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-21 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-21 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-21 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-21 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-21 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-21 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-21 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-21 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-21 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-21 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-21 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-21 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-21 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-21 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-21 div.sk-item {position: relative;z-index: 1;}#sk-container-id-21 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-21 div.sk-item::before, #sk-container-id-21 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-21 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-21 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-21 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-21 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-21 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-21 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-21 div.sk-label-container {text-align: center;}#sk-container-id-21 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-21 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-21\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>MLPRegressor(hidden_layer_sizes=(1000,), learning_rate=&#x27;adaptive&#x27;,\n",
              "             max_iter=5000)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-24\" type=\"checkbox\" checked><label for=\"sk-estimator-id-24\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">MLPRegressor</label><div class=\"sk-toggleable__content\"><pre>MLPRegressor(hidden_layer_sizes=(1000,), learning_rate=&#x27;adaptive&#x27;,\n",
              "             max_iter=5000)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "evaluate_model(final_model, X_train_scaled, X_test_scaled, y_train, y_test, scaler_y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 704
        },
        "id": "_ASvZmAA2hrU",
        "outputId": "aa522bab-9173-4c49-c7e1-58a44f823f3f"
      },
      "execution_count": 74,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training MSE: 0.14, Training MAE: 0.22\n",
            "Testing MSE: 0.33, Testing MAE: 0.31\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Decision Tree"
      ],
      "metadata": {
        "id": "UzpO-kjA1Fl5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.tree import DecisionTreeRegressor\n",
        "\n",
        "final_model = DecisionTreeRegressor(\n",
        "    max_depth=10,\n",
        "    min_samples_split=5,\n",
        "    min_samples_leaf=4,\n",
        "    random_state=42\n",
        ")\n",
        "final_model.fit(X_train_scaled, y_train_scaled.ravel())\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "jr1uijh01E2g",
        "outputId": "8910ea7a-78eb-464f-cadb-3de0b66d4f7a"
      },
      "execution_count": 75,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DecisionTreeRegressor(max_depth=10, min_samples_leaf=4, min_samples_split=5,\n",
              "                      random_state=42)"
            ],
            "text/html": [
              "<style>#sk-container-id-22 {color: black;}#sk-container-id-22 pre{padding: 0;}#sk-container-id-22 div.sk-toggleable {background-color: white;}#sk-container-id-22 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-22 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-22 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-22 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-22 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-22 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-22 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-22 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-22 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-22 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-22 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-22 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-22 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-22 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-22 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-22 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-22 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-22 div.sk-item {position: relative;z-index: 1;}#sk-container-id-22 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-22 div.sk-item::before, #sk-container-id-22 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-22 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-22 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-22 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-22 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-22 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-22 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-22 div.sk-label-container {text-align: center;}#sk-container-id-22 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-22 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-22\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeRegressor(max_depth=10, min_samples_leaf=4, min_samples_split=5,\n",
              "                      random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-25\" type=\"checkbox\" checked><label for=\"sk-estimator-id-25\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">DecisionTreeRegressor</label><div class=\"sk-toggleable__content\"><pre>DecisionTreeRegressor(max_depth=10, min_samples_leaf=4, min_samples_split=5,\n",
              "                      random_state=42)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 75
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "evaluate_model(final_model, X_train_scaled, X_test_scaled, y_train, y_test, scaler_y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 704
        },
        "id": "zqu5saVu2rN2",
        "outputId": "f0f27959-5f4c-410c-dd56-3c22dcca8441"
      },
      "execution_count": 76,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training MSE: 0.19, Training MAE: 0.18\n",
            "Testing MSE: 0.46, Testing MAE: 0.28\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Stacking ensable"
      ],
      "metadata": {
        "id": "6JSMhjgJ1OkX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.ensemble import StackingRegressor\n",
        "from sklearn.linear_model import Ridge\n",
        "\n",
        "base_models = [\n",
        "    ('xgb', XGBRegressor(\n",
        "        colsample_bytree=0.3,\n",
        "        learning_rate=0.1,\n",
        "        max_depth=3,\n",
        "        n_estimators=300,\n",
        "        subsample=0.5,\n",
        "        random_state=45\n",
        "    )),\n",
        "    ('rf', RandomForestRegressor(\n",
        "        max_depth=30,\n",
        "        max_features='log2',\n",
        "        min_samples_leaf=4,\n",
        "        min_samples_split=10,\n",
        "        n_estimators=100,\n",
        "        random_state=41\n",
        "    ))\n",
        "]\n",
        "\n",
        "final_model = StackingRegressor(\n",
        "    estimators=base_models,\n",
        "    final_estimator=Ridge(),\n",
        "    cv=5\n",
        ")\n",
        "final_model.fit(X_train_scaled, y_train_scaled.ravel())\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "e9lvddzF1N2g",
        "outputId": "ae9d19af-8920-4f5d-986d-e50fd38613ae"
      },
      "execution_count": 77,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "StackingRegressor(cv=5,\n",
              "                  estimators=[('xgb',\n",
              "                               XGBRegressor(base_score=None, booster=None,\n",
              "                                            callbacks=None,\n",
              "                                            colsample_bylevel=None,\n",
              "                                            colsample_bynode=None,\n",
              "                                            colsample_bytree=0.3, device=None,\n",
              "                                            early_stopping_rounds=None,\n",
              "                                            enable_categorical=False,\n",
              "                                            eval_metric=None,\n",
              "                                            feature_types=None, gamma=None,\n",
              "                                            grow_policy=None,\n",
              "                                            importance_type=None,\n",
              "                                            interaction_constraints=None,\n",
              "                                            learnin...\n",
              "                                            max_cat_to_onehot=None,\n",
              "                                            max_delta_step=None, max_depth=3,\n",
              "                                            max_leaves=None,\n",
              "                                            min_child_weight=None, missing=nan,\n",
              "                                            monotone_constraints=None,\n",
              "                                            multi_strategy=None,\n",
              "                                            n_estimators=300, n_jobs=None,\n",
              "                                            num_parallel_tree=None,\n",
              "                                            random_state=45, ...)),\n",
              "                              ('rf',\n",
              "                               RandomForestRegressor(max_depth=30,\n",
              "                                                     max_features='log2',\n",
              "                                                     min_samples_leaf=4,\n",
              "                                                     min_samples_split=10,\n",
              "                                                     random_state=41))],\n",
              "                  final_estimator=Ridge())"
            ],
            "text/html": [
              "<style>#sk-container-id-23 {color: black;}#sk-container-id-23 pre{padding: 0;}#sk-container-id-23 div.sk-toggleable {background-color: white;}#sk-container-id-23 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-23 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-23 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-23 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-23 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-23 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-23 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-23 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-23 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-23 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-23 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-23 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-23 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-23 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-23 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-23 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-23 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-23 div.sk-item {position: relative;z-index: 1;}#sk-container-id-23 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-23 div.sk-item::before, #sk-container-id-23 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-23 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-23 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-23 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-23 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-23 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-23 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-23 div.sk-label-container {text-align: center;}#sk-container-id-23 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-23 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-23\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>StackingRegressor(cv=5,\n",
              "                  estimators=[(&#x27;xgb&#x27;,\n",
              "                               XGBRegressor(base_score=None, booster=None,\n",
              "                                            callbacks=None,\n",
              "                                            colsample_bylevel=None,\n",
              "                                            colsample_bynode=None,\n",
              "                                            colsample_bytree=0.3, device=None,\n",
              "                                            early_stopping_rounds=None,\n",
              "                                            enable_categorical=False,\n",
              "                                            eval_metric=None,\n",
              "                                            feature_types=None, gamma=None,\n",
              "                                            grow_policy=None,\n",
              "                                            importance_type=None,\n",
              "                                            interaction_constraints=None,\n",
              "                                            learnin...\n",
              "                                            max_cat_to_onehot=None,\n",
              "                                            max_delta_step=None, max_depth=3,\n",
              "                                            max_leaves=None,\n",
              "                                            min_child_weight=None, missing=nan,\n",
              "                                            monotone_constraints=None,\n",
              "                                            multi_strategy=None,\n",
              "                                            n_estimators=300, n_jobs=None,\n",
              "                                            num_parallel_tree=None,\n",
              "                                            random_state=45, ...)),\n",
              "                              (&#x27;rf&#x27;,\n",
              "                               RandomForestRegressor(max_depth=30,\n",
              "                                                     max_features=&#x27;log2&#x27;,\n",
              "                                                     min_samples_leaf=4,\n",
              "                                                     min_samples_split=10,\n",
              "                                                     random_state=41))],\n",
              "                  final_estimator=Ridge())</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-26\" type=\"checkbox\" ><label for=\"sk-estimator-id-26\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">StackingRegressor</label><div class=\"sk-toggleable__content\"><pre>StackingRegressor(cv=5,\n",
              "                  estimators=[(&#x27;xgb&#x27;,\n",
              "                               XGBRegressor(base_score=None, booster=None,\n",
              "                                            callbacks=None,\n",
              "                                            colsample_bylevel=None,\n",
              "                                            colsample_bynode=None,\n",
              "                                            colsample_bytree=0.3, device=None,\n",
              "                                            early_stopping_rounds=None,\n",
              "                                            enable_categorical=False,\n",
              "                                            eval_metric=None,\n",
              "                                            feature_types=None, gamma=None,\n",
              "                                            grow_policy=None,\n",
              "                                            importance_type=None,\n",
              "                                            interaction_constraints=None,\n",
              "                                            learnin...\n",
              "                                            max_cat_to_onehot=None,\n",
              "                                            max_delta_step=None, max_depth=3,\n",
              "                                            max_leaves=None,\n",
              "                                            min_child_weight=None, missing=nan,\n",
              "                                            monotone_constraints=None,\n",
              "                                            multi_strategy=None,\n",
              "                                            n_estimators=300, n_jobs=None,\n",
              "                                            num_parallel_tree=None,\n",
              "                                            random_state=45, ...)),\n",
              "                              (&#x27;rf&#x27;,\n",
              "                               RandomForestRegressor(max_depth=30,\n",
              "                                                     max_features=&#x27;log2&#x27;,\n",
              "                                                     min_samples_leaf=4,\n",
              "                                                     min_samples_split=10,\n",
              "                                                     random_state=41))],\n",
              "                  final_estimator=Ridge())</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><label>xgb</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-27\" type=\"checkbox\" ><label for=\"sk-estimator-id-27\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">XGBRegressor</label><div class=\"sk-toggleable__content\"><pre>XGBRegressor(base_score=None, booster=None, callbacks=None,\n",
              "             colsample_bylevel=None, colsample_bynode=None,\n",
              "             colsample_bytree=0.3, device=None, early_stopping_rounds=None,\n",
              "             enable_categorical=False, eval_metric=None, feature_types=None,\n",
              "             gamma=None, grow_policy=None, importance_type=None,\n",
              "             interaction_constraints=None, learning_rate=0.1, max_bin=None,\n",
              "             max_cat_threshold=None, max_cat_to_onehot=None,\n",
              "             max_delta_step=None, max_depth=3, max_leaves=None,\n",
              "             min_child_weight=None, missing=nan, monotone_constraints=None,\n",
              "             multi_strategy=None, n_estimators=300, n_jobs=None,\n",
              "             num_parallel_tree=None, random_state=45, ...)</pre></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><label>rf</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-28\" type=\"checkbox\" ><label for=\"sk-estimator-id-28\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomForestRegressor</label><div class=\"sk-toggleable__content\"><pre>RandomForestRegressor(max_depth=30, max_features=&#x27;log2&#x27;, min_samples_leaf=4,\n",
              "                      min_samples_split=10, random_state=41)</pre></div></div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><label>final_estimator</label></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-29\" type=\"checkbox\" ><label for=\"sk-estimator-id-29\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">Ridge</label><div class=\"sk-toggleable__content\"><pre>Ridge()</pre></div></div></div></div></div></div></div></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 77
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "evaluate_model(final_model, X_train_scaled, X_test_scaled, y_train, y_test, scaler_y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 704
        },
        "id": "Hr9v9VR-2y9w",
        "outputId": "f059bf88-630f-4720-f2ea-3df0b3ca67ee"
      },
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training MSE: 0.14, Training MAE: 0.16\n",
            "Testing MSE: 0.36, Testing MAE: 0.25\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x300 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}