MLflow-example-notebook.ipynb

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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/caroheymes/mlflow_colab/blob/master/MLflow-example-notebook.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "y7wSVnqQ7xZB"
      },
      "source": [
        "# MLflow Example Notebook\n",
        "\n",
        "## Repo: https://github.com/alfozan/mlflow-example\n",
        "---\n",
        "\n",
        "This notebook demonstrates an example of dataset preprocessing, ML model training and evaluation, model tuning via MLflow tracking and finally REST API model serving via MLflow models.\n",
        "\n",
        "- **Talks:** https://twitter.com/PyDataRiyadh/status/1291043529146466304 and https://twitter.com/PyDataRiyadh/status/1314841078999154689?s=20\n",
        "- **Author:** Abdulrahman Alfozan ([@alfozan](https://twitter.com/alfozan)), [github](https://github.com/alfozan)\n",
        "---\n",
        "- **Dateset:** Bike Sharing Dataset: http://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset\n",
        "- **Goal:** predict `rented_bikes` (count per hour) based on weather and time information.\n",
        "\n",
        "\n",
        "**References:**\n",
        "- https://docs.databricks.com/_static/notebooks/gbt-regression.html\n",
        "- https://www.kaggle.com/pratsiuk/mlflow-experiment-automation-top-9\n",
        "- https://mlflow.org/docs/latest/tracking.html"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6dR-JRDBngFJ"
      },
      "source": [
        "# Import Libraries\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5C1LuP7Oodd8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3e964f4b-85d8-4aa5-9c49-5e2c32a6943e"
      },
      "source": [
        "!pip install mlflow --quiet\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "import mlflow\n",
        "import mlflow.sklearn\n",
        "from mlflow import log_metric, log_param, log_artifact\n",
        "\n",
        "from sklearn.ensemble import GradientBoostingRegressor\n",
        "from sklearn.metrics import mean_squared_error\n",
        "from sklearn.model_selection import KFold, cross_val_score, train_test_split\n",
        "from sklearn.inspection import permutation_importance\n",
        "from mlflow.models.signature import infer_signature\n",
        "from sklearn import tree\n",
        "\n",
        "from pydotplus import graph_from_dot_data\n",
        "import graphviz\n",
        "from IPython.display import Image\n",
        "\n",
        "import itertools\n",
        "\n",
        "plt.style.use(\"fivethirtyeight\")\n",
        "pd.plotting.register_matplotlib_converters()\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[K     |████████████████████████████████| 16.9 MB 69 kB/s \n",
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            "\u001b[K     |████████████████████████████████| 596 kB 38.3 MB/s \n",
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            "\u001b[K     |████████████████████████████████| 63 kB 1.7 MB/s \n",
            "\u001b[?25h  Building wheel for alembic (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for databricks-cli (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TwKZC40S-e0R"
      },
      "source": [
        "# Import Data\n",
        "\n",
        "Dataset and explanation:\n",
        "http://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset\n",
        "\n",
        "- Input file: `hour.csv` - contains bike sharing counts aggregated on hourly basis. \n",
        "- Size: 17379 hours / rows\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1SZF_ZgD-gez",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e275f533-5934-4b5b-e79a-187eb9b39bde"
      },
      "source": [
        "# download and extract csv files into Data folder\n",
        "!wget -nc \"http://archive.ics.uci.edu/ml/machine-learning-databases/00275/Bike-Sharing-Dataset.zip\"\n",
        "!unzip -o \"Bike-Sharing-Dataset.zip\""
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2021-11-01 16:07:44--  http://archive.ics.uci.edu/ml/machine-learning-databases/00275/Bike-Sharing-Dataset.zip\n",
            "Resolving archive.ics.uci.edu (archive.ics.uci.edu)... 128.195.10.252\n",
            "Connecting to archive.ics.uci.edu (archive.ics.uci.edu)|128.195.10.252|:80... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 279992 (273K) [application/x-httpd-php]\n",
            "Saving to: ‘Bike-Sharing-Dataset.zip’\n",
            "\n",
            "Bike-Sharing-Datase 100%[===================>] 273.43K   974KB/s    in 0.3s    \n",
            "\n",
            "2021-11-01 16:07:44 (974 KB/s) - ‘Bike-Sharing-Dataset.zip’ saved [279992/279992]\n",
            "\n",
            "Archive:  Bike-Sharing-Dataset.zip\n",
            "  inflating: Readme.txt              \n",
            "  inflating: day.csv                 \n",
            "  inflating: hour.csv                \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mFGzYdKCCNiK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "outputId": "8a624eaa-d521-4475-eacf-96c2ea9bc561"
      },
      "source": [
        "# load input data into pandas dataframe\n",
        "bike_sharing = pd.read_csv(\"hour.csv\")\n",
        "bike_sharing        "
      ],
      "execution_count": 3,
      "outputs": [
        {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>instant</th>\n",
              "      <th>dteday</th>\n",
              "      <th>season</th>\n",
              "      <th>yr</th>\n",
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              "      <th>windspeed</th>\n",
              "      <th>casual</th>\n",
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              "      <td>17378</td>\n",
              "      <td>2012-12-31</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>12</td>\n",
              "      <td>22</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>0.2727</td>\n",
              "      <td>0.56</td>\n",
              "      <td>0.1343</td>\n",
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              "      <td>48</td>\n",
              "      <td>61</td>\n",
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              "      <td>2012-12-31</td>\n",
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              "      <td>12</td>\n",
              "      <td>23</td>\n",
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              "      <td>1</td>\n",
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              "<p>17379 rows × 17 columns</p>\n",
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            ],
            "text/plain": [
              "       instant      dteday  season  yr  ...  windspeed  casual  registered  cnt\n",
              "0            1  2011-01-01       1   0  ...     0.0000       3          13   16\n",
              "1            2  2011-01-01       1   0  ...     0.0000       8          32   40\n",
              "2            3  2011-01-01       1   0  ...     0.0000       5          27   32\n",
              "3            4  2011-01-01       1   0  ...     0.0000       3          10   13\n",
              "4            5  2011-01-01       1   0  ...     0.0000       0           1    1\n",
              "...        ...         ...     ...  ..  ...        ...     ...         ...  ...\n",
              "17374    17375  2012-12-31       1   1  ...     0.1642      11         108  119\n",
              "17375    17376  2012-12-31       1   1  ...     0.1642       8          81   89\n",
              "17376    17377  2012-12-31       1   1  ...     0.1642       7          83   90\n",
              "17377    17378  2012-12-31       1   1  ...     0.1343      13          48   61\n",
              "17378    17379  2012-12-31       1   1  ...     0.1343      12          37   49\n",
              "\n",
              "[17379 rows x 17 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fQk3RQt2FB8x"
      },
      "source": [
        "## Data preprocessing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vyS5Ru5aE5Y7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "outputId": "106eb121-f94c-44bb-a9a1-75edd6ec2d53"
      },
      "source": [
        "# remove unused columns\n",
        "bike_sharing.drop(columns=[\"instant\", \"dteday\", \"registered\", \"casual\"], inplace=True)\n",
        "\n",
        "# use better names\n",
        "bike_sharing.rename(\n",
        "    columns={\n",
        "        \"yr\": \"year\",\n",
        "        \"mnth\": \"month\",\n",
        "        \"hr\": \"hour_of_day\",\n",
        "        \"holiday\": \"is_holiday\",\n",
        "        \"workingday\": \"is_workingday\",\n",
        "        \"weathersit\": \"weather_situation\",\n",
        "        \"temp\": \"temperature\",\n",
        "        \"atemp\": \"feels_like_temperature\",\n",
        "        \"hum\": \"humidity\",\n",
        "        \"cnt\": \"rented_bikes\",\n",
        "    },\n",
        "    inplace=True,\n",
        ")\n",
        "\n",
        "# show samples\n",
        "bike_sharing"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
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              "      <th>feels_like_temperature</th>\n",
              "      <th>humidity</th>\n",
              "      <th>windspeed</th>\n",
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              "      <td>0.24</td>\n",
              "      <td>0.2879</td>\n",
              "      <td>0.81</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.22</td>\n",
              "      <td>0.2727</td>\n",
              "      <td>0.80</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.22</td>\n",
              "      <td>0.2727</td>\n",
              "      <td>0.80</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.24</td>\n",
              "      <td>0.2879</td>\n",
              "      <td>0.75</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.24</td>\n",
              "      <td>0.2879</td>\n",
              "      <td>0.75</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17374</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>12</td>\n",
              "      <td>19</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.2576</td>\n",
              "      <td>0.60</td>\n",
              "      <td>0.1642</td>\n",
              "      <td>119</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17375</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>12</td>\n",
              "      <td>20</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.2576</td>\n",
              "      <td>0.60</td>\n",
              "      <td>0.1642</td>\n",
              "      <td>89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17376</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>12</td>\n",
              "      <td>21</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.2576</td>\n",
              "      <td>0.60</td>\n",
              "      <td>0.1642</td>\n",
              "      <td>90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17377</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>12</td>\n",
              "      <td>22</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.2727</td>\n",
              "      <td>0.56</td>\n",
              "      <td>0.1343</td>\n",
              "      <td>61</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17378</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>12</td>\n",
              "      <td>23</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.2727</td>\n",
              "      <td>0.65</td>\n",
              "      <td>0.1343</td>\n",
              "      <td>49</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>17379 rows × 13 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       season  year  month  ...  humidity  windspeed  rented_bikes\n",
              "0           1     0      1  ...      0.81     0.0000            16\n",
              "1           1     0      1  ...      0.80     0.0000            40\n",
              "2           1     0      1  ...      0.80     0.0000            32\n",
              "3           1     0      1  ...      0.75     0.0000            13\n",
              "4           1     0      1  ...      0.75     0.0000             1\n",
              "...       ...   ...    ...  ...       ...        ...           ...\n",
              "17374       1     1     12  ...      0.60     0.1642           119\n",
              "17375       1     1     12  ...      0.60     0.1642            89\n",
              "17376       1     1     12  ...      0.60     0.1642            90\n",
              "17377       1     1     12  ...      0.56     0.1343            61\n",
              "17378       1     1     12  ...      0.65     0.1343            49\n",
              "\n",
              "[17379 rows x 13 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "40MGTHbNFKTP"
      },
      "source": [
        "### Data Visualization "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bNZOegwGHzUR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 639
        },
        "outputId": "eebea986-0df8-4941-f736-d3bfedeafe9f"
      },
      "source": [
        "hour_of_day_agg = bike_sharing.groupby([\"hour_of_day\"])[\"rented_bikes\"].sum()\n",
        "\n",
        "hour_of_day_agg.plot(\n",
        "    kind=\"line\", \n",
        "    title=\"Total rented bikes by hour of day\",\n",
        "    xticks=hour_of_day_agg.index,\n",
        "    figsize=(15, 10),\n",
        ")"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f79d583aad0>"
            ]
          },
          "metadata": {},
          "execution_count": 5
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZMg_JKoUKq9j"
      },
      "source": [
        "## Prepare training and test data sets\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZwtDgaZ9Ktie",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8bb09261-a0e1-43c1-f86d-4b71b2e65ecc"
      },
      "source": [
        "# Split the dataset randomly into 70% for training and 30% for testing.\n",
        "X = bike_sharing.drop(\"rented_bikes\", axis=1)\n",
        "y = bike_sharing.rented_bikes\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, train_size=0.7, test_size=0.3, random_state=42)\n",
        "\n",
        "print(f\"Training samples: {X_train.size}\")\n",
        "print(f\"Test samples: {X_test.size}\")"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training samples: 145980\n",
            "Test samples: 62568\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HN0w6zFJSb87"
      },
      "source": [
        "# Evaluation Metrics\n",
        "\n",
        "Create evaluation methods to be used in training stage (next step)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eC1wzz_T_tSA"
      },
      "source": [
        "## Root Mean Square Error (RMSE)\n",
        "\n",
        "References: \n",
        "- https://medium.com/@xaviergeerinck/artificial-intelligence-how-to-measure-performance-accuracy-precision-recall-f1-roc-rmse-611d10e4caac\n",
        "- https://www.kaggle.com/residentmario/model-fit-metrics#Root-mean-squared-error-(RMSE)\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MhPcLCteQy6j"
      },
      "source": [
        "def rmse(y, y_pred):\n",
        "    return np.sqrt(mean_squared_error(y, y_pred))\n",
        "\n",
        "\n",
        "def rmse_score(y, y_pred):\n",
        "    score = rmse(y, y_pred)\n",
        "    print(\"RMSE score: {:.4f}\".format(score))\n",
        "    return score"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fZ3nr3D_AE85"
      },
      "source": [
        "### Cross-Validation RMSLE score\n",
        "\n",
        "cross-validation combines (averages) measures of fitness in prediction to derive a more accurate estimate of model prediction performance.\n",
        "\n",
        "Background: \n",
        "- https://en.wikipedia.org/wiki/Cross-validation_(statistics)\n",
        "- https://www.kaggle.com/carlolepelaars/understanding-the-metric-rmsle\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9H9CZAP2ASe6"
      },
      "source": [
        "def rmsle_cv(model, X_train, y_train):\n",
        "    kf = KFold(n_splits=3, shuffle=True, random_state=42).get_n_splits(X_train.values)\n",
        "    # Evaluate a score by cross-validation\n",
        "    rmse = np.sqrt(-cross_val_score(model, X_train.values, y_train, scoring=\"neg_mean_squared_error\", cv=kf))\n",
        "    return rmse\n",
        "\n",
        "\n",
        "def rmse_cv_score(model, X_train, y_train):\n",
        "    score = rmsle_cv(model, X_train, y_train)\n",
        "    print(\"Cross-Validation RMSE score: {:.4f} (std = {:.4f})\".format(score.mean(), score.std()))\n",
        "    return score"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ad0mABWEarsA"
      },
      "source": [
        "## Feature Importance\n",
        "\n",
        "Background: https://medium.com/bigdatarepublic/feature-importance-whats-in-a-name-79532e59eea3"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OZ7kzjbOWae8"
      },
      "source": [
        "def model_feature_importance(model):\n",
        "    feature_importance = pd.DataFrame(\n",
        "        model.feature_importances_,\n",
        "        index=X_train.columns,\n",
        "        columns=[\"Importance\"],\n",
        "    )\n",
        "\n",
        "    # sort by importance\n",
        "    feature_importance.sort_values(by=\"Importance\", ascending=False, inplace=True)\n",
        "\n",
        "    # plot\n",
        "    plt.figure(figsize=(12, 8))\n",
        "    sns.barplot(\n",
        "        data=feature_importance.reset_index(),\n",
        "        y=\"index\",\n",
        "        x=\"Importance\",\n",
        "    ).set_title(\"Feature Importance\")\n",
        "    # save image\n",
        "    plt.savefig(\"model_artifacts/feature_importance.png\", bbox_inches='tight')"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rYfCxPo8w-Gn"
      },
      "source": [
        "## Permutation Importance\n",
        "\n",
        "Background: https://www.kaggle.com/dansbecker/permutation-importance"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b_vzVVbGcS6M"
      },
      "source": [
        "def model_permutation_importance(model):\n",
        "    p_importance = permutation_importance(model, X_test, y_test, random_state=42, n_jobs=-1)\n",
        "\n",
        "    # sort by importance\n",
        "    sorted_idx = p_importance.importances_mean.argsort()[::-1]\n",
        "    p_importance = pd.DataFrame(\n",
        "        data=p_importance.importances[sorted_idx].T,\n",
        "        columns=X_train.columns[sorted_idx]\n",
        "    )\n",
        "\n",
        "    # plot\n",
        "    plt.figure(figsize=(12, 8))\n",
        "    sns.barplot(\n",
        "        data=p_importance,\n",
        "        orient=\"h\"\n",
        "    ).set_title(\"Permutation Importance\")\n",
        "\n",
        "    # save image\n",
        "    plt.savefig(\"model_artifacts/permutation_importance.png\", bbox_inches=\"tight\")"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VtQGsSNU8hWc"
      },
      "source": [
        "## Decision Tree Visualization\n",
        "\n",
        "Reference: https://towardsdatascience.com/visualizing-decision-trees-with-python-scikit-learn-graphviz-matplotlib-1c50b4aa68dc \n",
        "\n",
        "\n",
        "TODO: plot all trees"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rxKIpaE-g-b1"
      },
      "source": [
        "def model_tree_visualization(model):\n",
        "    # generate visualization\n",
        "    tree_dot_data = tree.export_graphviz(\n",
        "        decision_tree=model.estimators_[0, 0],  # Get the first tree,\n",
        "        label=\"all\",\n",
        "        feature_names=X_train.columns,\n",
        "        filled=True,\n",
        "        rounded=True,\n",
        "        proportion=True,\n",
        "        impurity=False,\n",
        "        precision=1,\n",
        "    )\n",
        "\n",
        "    # save image\n",
        "    graph_from_dot_data(tree_dot_data).write_png(\"model_artifacts/Decision_Tree_Visualization.png\")\n",
        "\n",
        "    # show tree\n",
        "    return graphviz.Source(tree_dot_data)"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "warpAv8RFSOI"
      },
      "source": [
        "# MLflow Tracking\n",
        "\n",
        "Reference: https://www.mlflow.org/docs/latest/cli.html#mlflow-ui\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1kU8w1TNGG4Y"
      },
      "source": [
        "## MLflow Logger"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kyQRcKslAwv-"
      },
      "source": [
        "# Track params and metrics\n",
        "def log_mlflow_run(model, signature):\n",
        "    # Auto-logging for scikit-learn estimators\n",
        "    # mlflow.sklearn.autolog()\n",
        "\n",
        "    # log estimator_name name\n",
        "    name = model.__class__.__name__\n",
        "    mlflow.set_tag(\"estimator_name\", name)\n",
        "\n",
        "    # log input features\n",
        "    mlflow.set_tag(\"features\", str(X_train.columns.values.tolist()))\n",
        "\n",
        "    # Log tracked parameters only\n",
        "    mlflow.log_params({key: model.get_params()[key] for key in parameters})\n",
        "\n",
        "    mlflow.log_metrics({\n",
        "        'RMSE_CV': score_cv.mean(),\n",
        "        'RMSE': score,\n",
        "    })\n",
        "\n",
        "    # log training loss\n",
        "    for s in model.train_score_:\n",
        "        mlflow.log_metric(\"Train Loss\", s)\n",
        "\n",
        "    # Save model to artifacts\n",
        "    mlflow.sklearn.log_model(model, \"model\", signature=signature)\n",
        "\n",
        "    # log charts\n",
        "    mlflow.log_artifacts(\"model_artifacts\")\n",
        "\n",
        "    # misc\n",
        "    # Log all model parameters\n",
        "    # mlflow.log_params(model.get_params())\n",
        "    # mlflow.log_param(\"Training size\", X_test.size)\n",
        "    # mlflow.log_param(\"Test size\", y_test.size)"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vGmHvdrMw_-U"
      },
      "source": [
        "## Initialize MLflow experiment"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "noNeZRbU_llh",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "67981800-7c88-4bb9-818a-a3a95f45e2e5"
      },
      "source": [
        "experiment_name = \"rented_bikes\"\n",
        "\n",
        "mlflow.set_experiment(experiment_name)\n",
        "mlflow.set_tracking_uri(\"./mlruns\")\n",
        "\n",
        "# delete default experiment if exits\n",
        "if (mlflow.get_experiment_by_name(\"Default\").lifecycle_stage == 'active'):\n",
        "    mlflow.delete_experiment(\"0\")\n",
        "\n",
        "# create model_artifacts directory \n",
        "!mkdir -p \"model_artifacts\""
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "INFO: 'rented_bikes' does not exist. Creating a new experiment\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UZScaIVhAPEj"
      },
      "source": [
        "## Start experiments tracking UI"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8IvEYLSPNUkA"
      },
      "source": [
        "# run tracking UI in the background\n",
        "get_ipython().system_raw(\"mlflow ui --port 5000 &\")"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "P8cfq8bO_LRr"
      },
      "source": [
        "### MLflow UI URL"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4h3bKHMYUIG6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "01427b19-46ec-4595-8a4e-38f23911e557"
      },
      "source": [
        "# create remote tunnel using ngrok.com to allow local port access\n",
        "!pip install pyngrok --quiet\n",
        "from pyngrok import ngrok\n",
        "\n",
        "# Terminate open tunnels if exist\n",
        "ngrok.kill()\n",
        "\n",
        "# Setting the authtoken (optional)\n",
        "# Get your authtoken from https://dashboard.ngrok.com/auth\n",
        "NGROK_AUTH_TOKEN = \"\"\n",
        "ngrok.set_auth_token(NGROK_AUTH_TOKEN)\n",
        "\n",
        "# Open an HTTPs tunnel on port 5000 for http://localhost:5000\n",
        "public_url = ngrok.connect(port=\"5000\", proto=\"http\", options={\"bind_tls\": True})\n",
        "print(\"MLflow Tracking UI:\", public_url)"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "\u001b[?25h  Building wheel for pyngrok (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "MLflow Tracking UI: NgrokTunnel: \"http://a663-34-75-144-171.ngrok.io\" -> \"http://localhost:80\"\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z1S4mo8_SE6K"
      },
      "source": [
        "Note: you can download `/content/mlruns` folder and run `mlflow ui` locally\n",
        "\n",
        "Steps:\n",
        "- Download `/content/mlruns` folder to `~/Downloads`\n",
        "- `cd ~/Downloads && pip install mlflow && mlflow ui`\n",
        "\n",
        "Reference: https://www.mlflow.org/docs/latest/quickstart.html#viewing-the-tracking-ui\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7xRa6vYWMed1"
      },
      "source": [
        "# Model Training\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mDAdPTeDTjr1"
      },
      "source": [
        "## Model Type & Method\n",
        "\n",
        "For this example,\n",
        "- Approache: Decision tree (Supervised learning)\n",
        "- Tree type: Regression tree\n",
        "- Technique/ensemble method: Gradient boosting\n",
        "\n",
        "**All put together we get:** [GBRT (Gradient Boosted Regression Tree)](https://orbi.uliege.be/bitstream/2268/163521/1/slides.pdf)\n",
        "\n",
        "Background:\n",
        "- Choosing a model: https://scikit-learn.org/stable/tutorial/machine_learning_map\n",
        "- Machine Learning Models Explained\n",
        ": https://docs.paperspace.com/machine-learning/wiki/machine-learning-models-explained\n",
        "- Gradient Boosted Regression Trees: https://orbi.uliege.be/bitstream/2268/163521/1/slides.pdf\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OSbcPvkBThXV"
      },
      "source": [
        "# GBRT (Gradient Boosted Regression Tree) scikit-learn implementation \n",
        "model_class = GradientBoostingRegressor"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "l7BYFTSRzLk2"
      },
      "source": [
        "## Model Hyper-parameters \n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1Mu88JOkMiJF"
      },
      "source": [
        "parameters = {\n",
        "    \"learning_rate\": [0.1, 0.05, 0.01],\n",
        "    \"max_depth\": [4, 5, 6],\n",
        "    # \"verbose\": True,\n",
        "}"
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LnUDX2p2j9p_"
      },
      "source": [
        "### Tuning the hyper-parameters: Grid search\n",
        "\n",
        "- Simple but inefficient\n",
        "- more advanced tuning techniques: https://research.fb.com/efficient-tuning-of-online-systems-using-bayesian-optimization/"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CybsVlgCw6n9"
      },
      "source": [
        "# generate parameters combinations\n",
        "params_keys = parameters.keys()\n",
        "params_values = [\n",
        "    parameters[key] if isinstance(parameters[key], list) else [parameters[key]]\n",
        "    for key in params_keys\n",
        "]\n",
        "runs_parameters = [\n",
        "    dict(zip(params_keys, combination)) for combination in itertools.product(*params_values)\n",
        "]"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u23-Tpn_0X7d"
      },
      "source": [
        "## Training runs"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Le6sa7jjg37v",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "21f3fa7c-99f9-4323-b947-d854be086f12"
      },
      "source": [
        "# training loop\n",
        "for i, run_parameters in enumerate(runs_parameters):\n",
        "    print(f\"Run {i}: {run_parameters}\")\n",
        "\n",
        "    # mlflow: stop active runs if any\n",
        "    if mlflow.active_run():\n",
        "        mlflow.end_run()\n",
        "    # mlflow:track run\n",
        "    mlflow.start_run(run_name=f\"Run {i}\")\n",
        "\n",
        "    # create model instance\n",
        "    model = model_class(**run_parameters)\n",
        "\n",
        "    # train\n",
        "    model.fit(X_train, y_train)\n",
        "\n",
        "    # get evaluations scores\n",
        "    score = rmse_score(y_test, model.predict(X_test))\n",
        "    score_cv = rmse_cv_score(model, X_train, y_train)\n",
        "    \n",
        "    # generate charts\n",
        "    model_feature_importance(model)\n",
        "    plt.close()\n",
        "    model_permutation_importance(model)\n",
        "    plt.close()\n",
        "    model_tree_visualization(model)\n",
        "\n",
        "    # get model signature\n",
        "    signature = infer_signature(model_input=X_train, model_output=model.predict(X_train))\n",
        "\n",
        "    # mlflow: log metrics\n",
        "    log_mlflow_run(model, signature)\n",
        "\n",
        "    # mlflow: end tracking\n",
        "    mlflow.end_run()\n",
        "    print(\"\")"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Run 0: {'learning_rate': 0.1, 'max_depth': 4}\n",
            "RMSE score: 52.0056\n",
            "Cross-Validation RMSE score: 56.5378 (std = 0.1629)\n",
            "\n",
            "Run 1: {'learning_rate': 0.1, 'max_depth': 5}\n",
            "RMSE score: 44.6871\n",
            "Cross-Validation RMSE score: 48.1899 (std = 0.1674)\n",
            "\n",
            "Run 2: {'learning_rate': 0.1, 'max_depth': 6}\n",
            "RMSE score: 41.8716\n",
            "Cross-Validation RMSE score: 44.9722 (std = 0.4243)\n",
            "\n",
            "Run 3: {'learning_rate': 0.05, 'max_depth': 4}\n",
            "RMSE score: 63.1486\n",
            "Cross-Validation RMSE score: 67.8204 (std = 1.7233)\n",
            "\n",
            "Run 4: {'learning_rate': 0.05, 'max_depth': 5}\n",
            "RMSE score: 53.0419\n",
            "Cross-Validation RMSE score: 55.9769 (std = 0.8647)\n",
            "\n",
            "Run 5: {'learning_rate': 0.05, 'max_depth': 6}\n",
            "RMSE score: 46.2829\n",
            "Cross-Validation RMSE score: 49.8209 (std = 0.5443)\n",
            "\n",
            "Run 6: {'learning_rate': 0.01, 'max_depth': 4}\n",
            "RMSE score: 120.1656\n",
            "Cross-Validation RMSE score: 123.9446 (std = 1.0540)\n",
            "\n",
            "Run 7: {'learning_rate': 0.01, 'max_depth': 5}\n",
            "RMSE score: 112.4922\n",
            "Cross-Validation RMSE score: 116.0879 (std = 0.9958)\n",
            "\n",
            "Run 8: {'learning_rate': 0.01, 'max_depth': 6}\n",
            "RMSE score: 106.2636\n",
            "Cross-Validation RMSE score: 109.3516 (std = 1.2057)\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tOHX6U3ABTSE"
      },
      "source": [
        "# Best Model Results"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I5jKy850zKtS"
      },
      "source": [
        "best_run_df = mlflow.search_runs(order_by=['metrics.RMSE_CV ASC'], max_results=1)\n",
        "if len(best_run_df.index) == 0:\n",
        "    raise Exception(f\"Found no runs for experiment '{experiment_name}'\")\n",
        "\n",
        "best_run = mlflow.get_run(best_run_df.at[0, 'run_id'])\n",
        "best_model_uri = f\"{best_run.info.artifact_uri}/model\"\n",
        "best_model = mlflow.sklearn.load_model(best_model_uri)"
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wHVM74A--4-C",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9d3b9202-f335-43aa-ce52-a9bf52dffa93"
      },
      "source": [
        "# print best run info\n",
        "print(\"Best run info:\")\n",
        "print(f\"Run id: {best_run.info.run_id}\")\n",
        "print(f\"Run parameters: {best_run.data.params}\")\n",
        "print(\"Run score: RMSE_CV = {:.4f}\".format(best_run.data.metrics['RMSE_CV']))\n",
        "print(f\"Run model URI: {best_model_uri}\")"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Best run info:\n",
            "Run id: 8593261beb2d401eb90f565821cd6c4a\n",
            "Run parameters: {'max_depth': '6', 'learning_rate': '0.1'}\n",
            "Run score: RMSE_CV = 44.9722\n",
            "Run model URI: file:///content/mlruns/1/8593261beb2d401eb90f565821cd6c4a/artifacts/model\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WmjSO3vhCP7u",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        },
        "outputId": "ca57ae16-1923-45d3-a8de-2fa57da2f000"
      },
      "source": [
        "model_feature_importance(best_model)"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ca3+3ju0PdRzq6fcnYGpHn0909LmxXR5KkiOBa9s+9/HYmcTO683s756AnYETBzguSZIkaRwxHI4fL0/yHzTf6a+AmSs6UJLraJac/n/DU5okSZKkVZ3hcAiSXA08sVfzm6pqYTfq6VRV3+Lxbz5d0bGmL7+XJEmSpPHEcDgEVfWC5feSJEmSpLHHt5VKkiRJkgyHkiRJkiTDoSRJkiQJw6EkSZIkCcOhJEmSJAnfVqqVMOngr3W7BI2SxYsXM2XKlG6XIUmSpBHkzKEkSZIkyXAoSZIkSTIcSpIkSZIwHEqSJEmSMBxKkiRJkjAcSpIkSZIwHEqSJEmS8HcOtRKu+vYbul2CRtgO+32z2yVIkiRplDhzKEmSJEkyHEqSJEmSDIeSJEmSJAyHkiRJkiQMh5IkSZIkDIeSJEmSJAyHkiRJkiQMh5IkSZIkDIeSJEmSJAyHkiRJkiQMh0OWZL0k7+x2HcuT5L1JntTtOiRJkiSNDYbDoVsP6Ho4TGOg7++9wJDCYZK1Vq4qSZIkSWOV4XDoPg5skmR+kuOSHJHkmiQLknwYIMnkJDcnmZXk50lOS7JnkjlJFifZvu13dJJTksxt29/Wc5EBxr0lyTeARcCzk5yQ5NokN3b0Owx4BnBJkkvatns6xt4vyax2e1aSLyW5GvjfJJskOT/JdUlmJ3neKHymkiRJkrrMmaKhOxKYWlXTkuwF7AdsDwQ4J8muwP8BmwL7A28BrgEOBHYG9gH+E9i3HW8rYAdgXWBekvOAqcCUfsadAhxcVVcBJPlAVf05yZrARUm2qqrPJnkfsHtV/WkQ9/QsYKeqejjJRcChVbU4yQuALwJ7rPjHJUmSJGksMByunL3af/Pa/Yk04e3/gCVVtRAgyY3ARVVVSRYCkzvG+H5V3Qfc187ybU8TIvsb91c9wbD1uiRvp/kuNwQ2BxYM8T7OaoPhRGAn4KwkPceeOMSxJEmSJI1BhsOVE+B/qurLj2lMJgPLOpoe6dh/hMd+7tVrzFrOuPd27G8MHA7MqKq/tEtFJ/RTa+d1evfpGXMN4K6qmtbPGJIkSZLGKZ85HLq7gSe32xcAb2ln3EjyzCRPG+J4r0oyIclTgd1olqAOdtyn0AS7pUmeDry0nzoB/pDk+e1LbF7dVyFV9VdgSZL92+smydZDvB9JkiRJY5Azh0NUVXe2L5ZZBPwIOB2Y2y7DvAd4I/DwEIZcAFwCrA98tKpuB25P8vzljVtVNySZB9wM/BqY03H4K8D5SW6vqt1pnpU8F7gDuJZmqWpfDgJOSHIUsDZwBnDDEO5HkiRJ0hhkOFwBVXVgr6bj++g2taP/zI7t2zqPAQuq6s19XOP45Y3be+xe7Z8DPtex/23g2330m9lrfwmwd19jSpIkSRq/XFYqSZIkSXLmsJuq6uhu1yBJkiRJ4MyhJEmSJAnDoSRJkiQJw6EkSZIkCcOhJEmSJAnDoSRJkiQJw6EkSZIkCcOhJEmSJAl/51ArYYf9vtntEiRJkiQNE2cOJUmSJEmGQ0mSJEmS4VCSJEmShOFQkiRJkoThUJIkSZKE4VCSJEmShD9loZVwxjmv63YJGgav3+fMbpcgSZKkVYAzh5IkSZIkw6EkSZIkyXAoSZIkScJwKEmSJEnCcChJkiRJwnAoSZIkScJwKEmSJEnCcChJkiRJwnAoSZIkScJwKEmSJEnCcChJkiRJwnCoQUiyZrdrkCRJkjSyDIfjTJKPJHlvx/4xSd6T5Igk1yRZkOTDHce/l+S6JDcmeXtH+z1JPpnkBmDHUb4NSZIkSaPMcDj+nAS8GSDJGsDrgd8DU4DtgWnA9CS7tv3fUlXTge2Aw5I8tW1fF7i6qrauqitG8wYkSZIkjb61ul2AhldV3ZbkziTbAE8H5gEzgL3abYCJNGHxcppA+Oq2/dlt+53Aw8B3RrN2SZIkSd1jOByfvgrMBP6JZibxxcD/VNWXOzsl2Q3YE9ixqv6W5FJgQnv4/qp6eLQKliRJktRdLisdn84G9qaZMbyg/feWJBMBkjwzydOAScBf2mD4PGCHbhUsSZIkqbucORyHquqBJJcAd7Wzfz9O8nxgbhKAe4A3AucDhya5CbgFuKpbNUuSJEnqLsPhONS+iGYHYP+etqo6Hji+j+4v7WuMqpo4MtVJkiRJWhW5rHScSbI58Avgoqpa3O16JEmSJI0NzhyOM1X1M+C53a5DkiRJ0tjizKEkSZIkyXAoSZIkSTIcSpIkSZIwHEqSJEmSMBxKkiRJkjAcSpIkSZIwHEqSJEmS8HcOtRJev8+Z3S5BkiRJ0jBx5lCSJEmSZDiUJEmSJBkOJUmSJEkYDiVJkiRJGA4lSZIkSRgOJUmSJEn4UxZaCe+9+IBul7DSPrPHt7pdgiRJkrRKcOZQkiRJkmQ4lCRJkiQZDiVJkiRJGA4lSZIkSRgOJUmSJEkYDiVJkiRJGA4lSZIkSRgOJUmSJEkYDiVJkiRJGA4lSZIkSRgOJUmSJEmMUjhMcliSm5KcNsTzJidZtALXu6f9+4wk3263Zyb5/FDH6jXue5M8aWXGGA1J9k2yebfrkCRJkjR2jNbM4TuBl1TVQaN0PQCq6vaq2m8Yh3wvsEqEwyRrDnB4X2BI4TDJWitXkSRJkqSxbMTDYZIvAc8FfpTkA0lOSvLTJPOSvKrts2aS45Jck2RBkn/tY5wt2vPmt32mDOLafc48Jnl5krlJ1k+yV7t9fZKzkkzsZ6zDgGcAlyS5pG3r89wktyX5n7bWa5Nsm+SCJLcmObTts1uSy5Ocl+SWJF9KssYgxj02yfXA/kne1n5mNyT5TpInJdkJ2Ac4rr3+JkkuTbJdO8b6SW5rt2cmOSfJxcBFSdbt6/uRJEmSNP6NeDisqkOB24HdgXWBi6tq+3b/uCTrAm8FllbVDGAG8LYkG/ca6lDg+KqaBmwH/GZF6knyauBI4GVt01HAnlW1LXAt8L5+7uOzPfdRVbsnWX855/5fW+tsYBawH7AD8OGOPtsD76aZ5dsEeM0gxr2zqratqjOA71bVjKraGrgJeGtVXQmcAxxRVdOq6tblfCTbAvtV1YuAD9D39yNJkiRpnBvtpYR7AfskObzdnwA8p23fKknPEtBJwBTg5x3nzgU+kORZNKFo8Qpcfw+aYLlXVf01yStogtmcJABPaK8zGDss59xz2r8LgYlVdTdwd5JlSdZrj/20qn4JkOSbwM7A/csZ91sd21OTfAxYD5gIXDDI2jtdWFV/brf7+35uWoFxJUmSJI0hox0OA7y2qm55TGOTgt5dVRf0ap/cs11Vpye5Gng58MMk/1pVFw/x+rfSLHHdjGZGLjTh6A1DvZFBnLus/ftIx3bPfs/nXr3OqUGMe2/H9ixg36q6IclMYLd+znmIR2eJJwwwXp/fjyRJkqTxb7R/yuIC4N1tGCTJNh3t70iydtu+We/ljEmeC/yyXd75fWCrFbj+r4DXAt9IsgVwFfDCJJu211g3yWYDnH838OR2e6jn9mX7JBu3zxoeAFwxxHGfDPyu/dw6X/bTWSfAbcD0dnugF/T09/1IkiRJGudGOxx+FFgbWJDkxnYf4KvAz4Dr2xfIfJnHz2q+DliUZD4wFfjGihRQVTfTBKmzgKcAM4FvJllAs3zzeQOc/hXg/CSXVNUdQzy3L9cAn6dZtrkEOHuI4/4XcDUwB7i5o/0M4Ij2pTKbAJ+gCd/zgPUHqKe/70eSJEnSOJeq3isbNRqS7AYcXlWv6HYtQ7F06dK//wfz3osP6GYpw+Ize3xr+Z3E4sWLmTJluS8I1jjid7568fte/fidr178vlc//X3nkyZNykDnjfbMoSRJkiRpFTRmf/g8yVOBi/o49OKqunMlxz4b6P1TGv/e+4U5K6OqLgUuHa7xJEmSJGlljNlw2AbAaSM09qtHYlxJkiRJWlW5rFSSJEmSZDiUJEmSJBkOJUmSJEkYDiVJkiRJGA4lSZIkSYzht5Wq+/wBeUmSJGn8cOZQkiRJkmQ4lCRJkiQZDiVJkiRJGA4lSZIkSRgOJUmSJEkYDiVJkiRJ+FMWWgkHXvyVUb/m6Xu8fdSvKUmSJK0OnDmUJEmSJBkOJUmSJEmGQ0mSJEkShkNJkiRJEoZDSZIkSRKGQ0mSJEkShkNJkiRJEoZDSZIkSRKGQ0mSJEkShkNJkiRJEoZDSZIkSRKGQ0mSJEkShkNJkiRJEobDVVqSdZOcl+SGJIuSHJBkepLLklyX5IIkG7Z935bkmrbvd5I8qW3fvz33hiSXt20TkpycZGGSeUl2b9tnJvlukvOTLE7yv927e0mSJEmjyXC4atsbuL2qtq6qqcD5wOeA/apqOnAScEzb97tVNaOqtgZuAt7atn8Q+H/a9n3atncBVVVbAm8Avp5kQntsGnAAsCVwQJJnj+wtSpIkSVoVrNXtAjSghcAnkxwLnAv8BZgKXJgEYE3gd23fqUk+BqwHTAQuaNvnALOSnAl8t23bmSZkUlU3J/kVsFl77KKqWgqQ5GfARsCvR+wOJUmSJK0SDIersKr6eZJtgZcBHwMuBm6sqh376D4L2LeqbkgyE9itHePQJC8AXg5cl2T6ci67rGP7YfxvRJIkSVotuKx0FZbkGcDfqupU4DjgBcAGSXZsj6+dZIu2+5OB3yVZGzioY4xNqurqqvogcAfwbGB2T58kmwHPAW4ZpduSJEmStApyVmjVtiVwXJJHgAeBdwAPAZ9NMonm+/sMcCPwX8DVNAHwapqwSHv+FCDARcANwM3ACUkWtuPNrKpl7VJVSZIkSauhQYfDJE+tqjv7aN+kqm4d3rIEUFUX8Oizg5127aPvCcAJfbS/po/z7wcO6aPvLJrlqT37rxh8tZIkSZLGsqEsK12U5KWdDUneQTNLJUmSJEkaw4YSDt8CfDXJF5NsmuRHwKHAHiNTmiRJkiRptAw6HFbVj2iegduZ5uUldwIzqmrBCNUmSZIkSRolgw6HSSYCnwAmAZ+m+XmFmSNTliRJkiRpNA1lWekCYG1gq6o6nGY56buTnDsilUmSJEmSRs1QwuGRVfWmqloKUFXzgRnAz0ekMkmSJEnSqBnKM4dntj+6vkuSA9rmNWl+X0+SJEmSNIYN5ZnDLWlmCU8EvtY2vwg4aQTqkiRJkiSNorWG0PcE4INVdUqSv7Rtl9GERa2GTt/j7d0uQZIkSdIwGcozh1sAp7bbBVBV9wLrDHdRkiRJkqTRNZRweBswvbMhyfbAL4azIEmSJEnS6BvKstL/As5L8iXgCUn+AzgUeNuIVCZJkiRJGjVDeVvpucDewAY0zxpuBLymqn48QrVJkiRJkkbJUGYOqap5wDtHqBZJkiRJUpcMGA6TfGQwg1TVB4enHEmSJElSNyxv5vDZHdsTgNcC1wC/Ap4DbA98Z2RK06ruoAvPHdbxTnvJK4Z1PEmSJEmDN2A4rKpDeraTnAG8oaq+09H2GmD/kStPkiRJkjQahvJTFi8Fvter7RzgZcNXjiRJkiSpG4YSDn8BvKtX2zuAW4evHEmSJElSNwzlbaX/Apyd5P3Ab4FnAg8BrxmJwiRJkiRJo2fQ4bCq5iWZAuwIbAj8DphbVQ+OVHGSJEmSpNEx1N85fBC4PMnfl6MmWaOqHhn2yiRJkiRJo2bQzxwm2TbJ3CT3Ag+2/x5q/0qSJEmSxrChzBx+HfgB8BbgbyNTjiRJkiSpG4YSDjcCPlBVNVLFSJIkSZK6Yyg/ZXE2sNdIFSJJkiRJ6p6hzBxOoPkpiyuA33ceqKo3D2tVkiRJkqRRNZSZw58BxwJzaH74vvOfVkCSyUkWjcC4H0myZx/tuyU5t93eJ8mR7fa+STYf7jokSZIkjR0Dzhwm2bWqLm93Z49CPRoGVfXBQfQ5Bzin3d0XOJfmfwBIkiRJWg0tb1npF4Gp7fbX+ulTwHOHraLVz5pJTgR2An4LvAr4EXB4VV2bZH3g2qqanGQmTZBbF5gCfAJ4AvAmYBnwsqr6c5JZwLlV9e0kewOfoXnD7BU9F23H2g44HdgHeFGSo4DXAmdV1bZtvynAt3r2JUmSJI1PAy4rraqpHdsb9/PPYLhypgBfqKotgLtowtlApgKvAWYAxwB/q6ptgLnAY579TDIBOBF4JTAd+MBXU0EAABphSURBVKfeg1XVlTQziEdU1bSquhVYmmRa2+UQ4OQVvDdJkiRJY8RQnjnUyFhSVfPb7euAycvpf0lV3V1VdwBLaX57EmBhH+c+rx1/cfsTJKcOsqavAockWRM4gGZ2UZIkSdI4ZjjsvmUd2w/TLPV9iEe/mwkD9H+kY/8Rhvb22YF8B3gp8Arguqq6c5jGlSRJkrSKMhyumm6jWQYKsN9KjHMzMDnJJu3+G/rpdzfw5J6dqrofuAA4AZeUSpIkSasFw+Gq6RPAO5LMA9Zf0UHakPd24Lwk1wN/7KfrGcARSeZ1BMnTaGYjf7yi15ckSZI0dgzXMkStgKq6jUffBktVfaLj8FYd20e1x2cBszr6T+7Y/vuxqprZ0X4+zbOHva/d2X8O0Pt3DncGTq6qhwd5O5IkSZLGMMOhHifJ2cAmwB7drkWSJEnS6DAc6nGq6tXdrkGSJEnS6PKZQ0mSJEmS4VCSJEmSZDiUJEmSJGE4lCRJkiRhOJQkSZIkYTiUJEmSJOFPWWglnPaSV3S7BEmSJEnDxJlDSZIkSZLhUJIkSZJkOJQkSZIkYTiUJEmSJGE4lCRJkiRhOJQkSZIkYTiUJEmSJOHvHGolHHzhtcM21tdfst2wjSVJkiRp6Jw5lCRJkiQZDiVJkiRJhkNJkiRJEoZDSZIkSRKGQ0mSJEkShkNJkiRJEoZDSZIkSRKGQ0mSJEkShkNJkiRJEoZDSZIkSRKGQ0mSJEkShsM+JZmZ5Bkd+7clWX+Urv3DJOu1/965kmP1vo+vJtl85auUJEmSNN4YDvs2E3jG8joNRpK1htK/ql5WVXcB6wErFQ7pdR9V9S9V9bOVHFOSJEnSODQuwmGSI5Ic1m5/OsnF7fYeSU5LsleSuUmuT3JWkont8Q8muSbJoiRfSWM/YDvgtCTzk6zTXubd7fkLkzyvPX/dJCcl+WmSeUle1bbPTHJOW8dF/dS8YZLL22ssSrJL294zS/lxYJP2+HFJdktybsf5n08ycyj3keTSJNu157yhvZdFSY7tGPeeJMckuSHJVUmePkxfkyRJkqRV2LgIh8BsYJd2eztgYpK127YFwFHAnlW1LXAt8L627+erakZVTQXWAV5RVd9u+xxUVdOq6r6275/a808ADm/bPgBcXFXbA7sDxyVZtz22LbBfVb2on5oPBC6oqmnA1sD8XsePBG5tazhiOfc/lPugXWp6LLAHMA2YkWTf9vC6wFVVtTVwOfC25VxbkiRJ0jgwXsLhdcD0JE8BlgFzaULiLsB9wObAnCTzgYOBjdrzdk9ydZKFNEFpiwGu8d2Oa01ut/cCjmzHvRSYADynPXZhVf15gPGuAQ5JcjSwZVXdPbhb7dNQ7gNgBnBpVd1RVQ8BpwG7tsceAHpmKDvvVZIkSdI4NqTn4VZVVfVgkiU0z9hdSTNbuDuwKbCEJqi9ofOcJBOALwLbVdWv25A2YYDLLGv/Psyjn1uA11bVLb3GfgFw73JqvjzJrsDLgVlJPlVV3xjglId4bJifsIL3sTwPVlW12533KkmSJGkcGy8zh9AsLT2cZinkbOBQYB5wFfDCJJvC358T3IxHA9Sf2mcQ9+sY627gyYO45gU0zyKmHXubwRabZCPgD1V1IvBVmmWonXrX8Ctg8yRPTLIe8OK2fUXu46fAi5Ksn2RN4A3AZYOtXZIkSdL4M55mhWbTPAM4t6ruTXI/MLuq7mhf3PLNJE9s+x5VVT9PciKwCPg9zTLPHrOALyW5D9hxgGt+FPgMsCDJGjSzlK8YZL27AUckeRC4B3hz58GqujPJnCSLgB9V1RFJzmzrXUITfKmqu4Z6H1X1uyRHApfQzH6eV1XfH2TdkiRJksahPLqCUFq+pUuX/v0/mIMvvHbYxv36S7YbtrE0/BYvXsyUKVO6XYZGkd/56sXve/Xjd7568fte/fT3nU+aNCkDnTeelpVKkiRJklbQeFpWukpKsiVwSq/mZVX1gm7UI0mSJEl9MRyOsKpaSPNbgpIkSZK0ynJZqSRJkiTJcChJkiRJMhxKkiRJkjAcSpIkSZIwHEqSJEmS8G2lWgn+cL0kSZI0fjhzKEmSJEkyHEqSJEmSDIeSJEmSJAyHkiRJkiQMh5IkSZIkDIeSJEmSJPwpC62E/7r4r4Pu+9E9njKClUiSJElaWc4cSpIkSZIMh5IkSZIkw6EkSZIkCcOhJEmSJAnDoSRJkiQJw6EkSZIkCcOhJEmSJAnDoSRJkiQJw6EkSZIkCcOhJEmSJAnD4WovyXpJ3tmxv1uSc7tZkyRJkqTRZzjUesA7l9tLkiRJ0rhmOBxDkkxOcnOSWUl+nuS0JHsmmZNkcZLtk/xjku8lWZDkqiRbteceneSkJJcm+WWSw9phPw5skmR+kuPatolJvt1e67Qk6coNS5IkSRo1a3W7AA3ZpsD+wFuAa4ADgZ2BfYD/BH4NzKuqfZPsAXwDmNae+zxgd+DJwC1JTgCOBKZW1TRolpUC2wBbALcDc4AXAleMxs1JkiRJ6g5nDseeJVW1sKoeAW4ELqqqAhYCk2mC4ikAVXUx8NQkT2nPPa+qllXVn4A/Ak/v5xo/rarftNeY344rSZIkaRwzHI49yzq2H+nYf4TlzwR3nvvwAP0H20+SJEnSOGE4HH9mAwfB35eI/qmq/jpA/7tplplKkiRJWo05IzT+HA2clGQB8Dfg4IE6V9Wd7QttFgE/As4b+RIlSZIkrWoMh2NIVd0GTO3Yn9nPsX37OPfoXvud4xzYq/ulHcf+bYULliRJkjRmuKxUkiRJkmQ4lCRJkiQZDiVJkiRJGA4lSZIkSRgOJUmSJEkYDiVJkiRJGA4lSZIkSRgOJUmSJEkYDiVJkiRJwFrdLkBj10f3eEq3S5AkSZI0TJw5lCRJkiQZDiVJkiRJhkNJkiRJEoZDSZIkSRKGQ0mSJEkShkNJkiRJEv6UhVbClec/OKh+O+299ghXIkmSJGllOXMoSZIkSTIcSpIkSZIMh5IkSZIkDIeSJEmSJAyHkiRJkiQMh5IkSZIkDIeSJEmSJAyHkiRJkiQMh5IkSZIkDIeSJEmSJAyH40aSS5Nst5w+M5N8frRqkiRJkjR2GA4lSZIkSYbDbklyRJLD2u1PJ7m43d4jyWlJ9koyN8n1Sc5KMrE9Pj3JZUmuS3JBkg17jbtGkllJPtbuH5Lk50l+Crywo98rk1ydZF6SnyR5envu4iQbdIz1i559SZIkSeOX4bB7ZgO7tNvbAROTrN22LQCOAvasqm2Ba4H3tcc/B+xXVdOBk4BjOsZcCzgNWFxVR7XB8cM0oXBnYPOOvlcAO1TVNsAZwPur6hHgVOCgts+ewA1Vdcfw3rokSZKkVc1a3S5gNXYdMD3JU4BlwPU0IXEX4ByaIDcnCcATgLnAPwNTgQvb9jWB33WM+WXgzKrqCYwvAC7tCXdJvgVs1h57FvCtNkA+AVjStp8EfB/4DPAW4ORhvWtJkiRJqyTDYZdU1YNJlgAzgStpZgt3BzalCWoXVtUbOs9JsiVwY1Xt2M+wVwK7J/lkVd2/nBI+B3yqqs5JshtwdFvXr5P8IckewPY8OosoSZIkaRxzWWl3zQYOBy5vtw8F5gFXAS9MsilAknWTbAbcAmyQZMe2fe0kW3SM9zXgh8CZSdYCrgZelOSp7ZLU/Tv6TgJ+224f3Kuur9IsLz2rqh4etruVJEmStMoyHHbXbGBDYG5V/QG4H5jdLgOdCXwzyQKaJaXPq6oHgP2AY5PcAMwHduocsKo+RRMwTwH+QDMjOBeYA9zU0fVo4Kwk1wF/6lXXOcBEXFIqSZIkrTZcVtpFVXURsHbH/mYd2xcDM/o4Zz6wax/tu3Vsf6jj0Mn0EfKq6vs0zxb2ZWuaF9HcvNybkCRJkjQuGA71GEmOBN6BzxpKkiRJqxWXleoxqurjVbVRVV3R7VokSZIkjR7DoSRJkiTJcChJkiRJMhxKkiRJkjAcSpIkSZIwHEqSJEmSMBxKkiRJkjAcSpIkSZKAtbpdgMaunfZeu9slSJIkSRomzhxKkiRJkgyHkiRJkiTDoSRJkiQJw6EkSZIkCcOhJEmSJAnDoSRJkiQJw6FWwl9Ovo+/nHxft8uQJEmSNAwMh5IkSZIkw6EkSZIkyXAoSZIkScJwKEmSJEnCcChJkiRJwnAoSZIkScJwKEmSJEnCcChJkiRJwnAoSZIkScJwKEmSJEnCcChJkiRJwnA46pL8MMl6Q+g/OcmikaxpgGvf043rSpIkSRp9a3W7gNVNVb2s2zVIkiRJUm/OHA6zJEckOazd/nSSi9vtPZKcluS2JOu3M4I3JTkxyY1Jfpxknbbv9CQ3JLkBeFfH2Fsk+WmS+UkWJJnSjnNzO/ZNSb6d5Ekd41yW5LokFyTZsG3fJMn5bfvsJM9r2zdOMjfJwiQfG+WPTpIkSVIXGQ6H32xgl3Z7O2BikrXbtst79Z0CfKGqtgDuAl7btp8MvLuqtu7V/1Dg+Kqa1o79m7b9n4EvVtXzgb8C72yv+Tlgv6qaDpwEHNP2/0o7/nTgcOCLbfvxwAlVtSXwuxX9ACRJkiSNPYbD4XcdMD3JU4BlwFyaILcLTXDstKSq5necN7l9HnG9quoJkqd09J8L/GeSfwc2qqr72vZfV9WcdvtUYGeawDgVuDDJfOAo4FlJJgI7AWe17V8GNmzPfSHwzT6uK0mSJGmc85nDYVZVDyZZAswErgQWALsDmwI39eq+rGP7YWCd5Yx9epKrgZcDP0zyr8AvgerdFQhwY1Xt2HmgDa13tbOPfV5moBokSZIkjU/OHI6M2TTLNS9vtw8F5lXVcoNXVd0F3JVk57bpoJ5jSZ4L/LKqPgt8H9iqPfScJD0h8EDgCuAWYIOe9iRrJ9miqv4KLEmyf9ueJD3LV+cAr+99XUmSJEnjn+FwZMymWao5t6r+ANzP45eUDuQQ4Avtss90tL8OWNS2TwW+0bbfArwryU3AP9A8N/gAsB9wbPtim/k0y0mhCX5vbdtvBF7Vtr+nHWch8Myh3LAkSZKksc1lpSOgqi4C1u7Y36xje3K7+SeagNfT/omO7euAzpfRvL9t/zjw8c5rtctEH6qqN/ZRx3xg1z7alwB799PeuQz1qL7uT5IkSdL448yhJEmSJMmZw7Guqm6jYwZSkiRJklaEM4eSJEmSJMOhJEmSJMlwKEmSJEnCcChJkiRJwnAoSZIkScJwKEmSJEnCn7LQSviHQ9bpdgmSJEmShokzh5IkSZIkw6EkSZIkyXAoSZIkScJwKEmSJEnCcChJkiRJwnAoSZIkScJwKEmSJEnCcKiVcP+sn3W7BEmSJEnDxHAoSZIkSTIcSpIkSZIMh5IkSZIkDIeSJEmSJAyHkiRJkiQMh9L/397dB9lV13ccf3/KFtLhIQj0QTSwrRI7YgEFsVJxqLUdqhCqUh5UamrVUpvamYp9gqEURq061YHqjA5YA1FEyWgnNdbIqDQChkY0RJ4qlAcT2gKNIZGmPAS//eOeHY/bze5Jcvfe3O37NbOzv3t+v3Pud/e7Z3e/9/c750qSJEnC4lCSJEmShMWhJEmSJAmLQ0mSJEkSFoeSJEmSJCwOJUmSJElYHA5Ekpt2YZ/HdnL8RUnOa9oXJ3nlFGNOSvKFnY1FkiRJ0tw3NuwA/j+oqhMG/HwXDvL5JEmSJI0+Zw4HYGIWMMkzk6xOsi7JbUlOnGG/dye5NcmaJD/bbBtP8tUk65N8JclhU+y3NMnpTfvkJHcl+Rbw2taY45N8I8m3k9yU5HnN9tVJjmmNuyHJ0X35RkiSJEnaY1kcDtbrgVVVdQxwNLBumrH7Amuq6mhgNfDWZvvfAVdW1VHAp4DLdnSAJPOAy4FTgWOBn2t13wWcWFUvBC4E3tNs/ziwuNl/ITCvqm7dia9RkiRJ0giyOBystcDvJrkI+KWq+sE0Y58EJq4PvAUYb9ovBa5u2suAl01zjF8E7ququ6uqgE+2+uYD1ya5DfgQcGSz/VrglCQ/CbwZWDrzlyVJkiRp1FkcDlBVrQZeDjwILE3yO9MMf6op6ACepv/Xh14CfK2qXkBvZnFeE+M24DrgNOAMerOTkiRJkuY4i8MBSnI48FBVXQ5cAbxoFw5zE3BW034D8PVpxt4FjCd5TvP47FbffHpFKjTLSFuuoLdcdW1Vbd6FGCVJkiSNGIvDwToJuDXJt4EzgUt34Rh/RG9p6nrgHOCPdzSwqh4H3gasbG5I83Cr+/3Ae5tYxibtdwuwFfjELsQnSZIkaQT5VhYDUFX7NZ+vBK7cmX2a9nJgedN+AHjFFOMvarUXt9pfonft4eTx3wAWtjZdMNFIcii9Fw6+3CVWSZIkSaPPmUP9mOY6yJuB86vqh8OOR5IkSdJgOHM4ZEluBvaZtPmcqvrOMOKpqquAq4bx3JIkSZKGx+JwyKrqJcOOQZIkSZJcVipJkiRJsjiUJEmSJFkcSpIkSZKwOJQkSZIkYXEoSZIkScLiULth3uLnDzsESZIkSX1icShJkiRJIlU17Bg0QrZs2eIPjCRJkjSC5s+fn+n6nTmUJEmSJFkcSpIkSZJcVipJkiRJwplDSZIkSRIWh5IkSZIkLA41jSQnJ/nXJPck+fMp+vdJ8pmm/+Yk44OPUv3UIecvT/KtJNuTnD6MGNU/HfL9J0nuSLI+yVeSHD6MONU/HXJ+bpLvJFmX5IYkvqHtCJsp361xr0tSSY4bZHzqvw7n+OIkjzTn+LokbxlGnOqPLud4kjOav+W3J7l6xmN6zaGmkmQv4LvArwMbgbXA2VV1R2vM24GjqurcJGcBr6mqM4cSsHZbx5yPAwcA5wErqmr54CNVP3TM968CN1fVtiR/AJzkOT66Oub8gKra2rQXAW+vqpOHEa92T5d8N+P2B1YCewNLquqbg45V/dHxHF8MHFdVS4YSpPqmY76PAD4LvKKqNif5map6eLrjOnOoHTkeuKeq7q2qJ4FrgNMmjTkNuLJpLwd+Lcm0752iPdqMOa+q+6tqPfDDYQSovuqS769V1bbm4Rrg2QOOUf3VJedbWw/3BXwFeXR1+TsOcAnwPuDxQQanWdE155obuuT7rcBHqmozwEyFIVgcaseeBWxoPd7YbJtyTFVtB7YABw8kOs2GLjnX3LGz+f494J9mNSLNtk45T/KHSf4NeD/wjgHFpv6bMd9JXgQsqKqVgwxMs6br7/XXNZcLLE+yYDChaRZ0yfdCYGGSG5OsSTLjShCLQ0nStJK8ETgO+MCwY9Hsq6qPVNVzgD8DLhh2PJodSX4C+CDwzmHHooH6R2C8qo4CruNHK8A0N40BRwAnAWcDlyc5cLodLA61Iw8C7VeTnt1sm3JMkjFgPrBpINFpNnTJueaOTvlO8krgfGBRVT0xoNg0O3b2HL8G+K1ZjUizaaZ87w+8ALg+yf3ALwMrvCnNSJvxHK+qTa3f5VcAxw4oNvVfl9/pG+ndI+KpqrqP3jWKR0x3UItD7cha4IgkP59kb+AsYMWkMSuANzXt04Gvlnc4GmVdcq65Y8Z8J3kh8DF6heGM1yloj9cl5+1/Gl4N3D3A+NRf0+a7qrZU1SFVNV5V4/SuK17kDWlGWpdz/Jmth4uAOwcYn/qry/9t/0Bv1pAkh9BbZnrvdAcd63+cmguqanuSJcAqYC/g76vq9iQXA9+sqhXAx4FlSe4Bvk/vh1IjqkvOk7wY+DzwDODUJH9dVUcOMWztoo7n+AeA/YBrm3tNfa+qFg0taO2Wjjlf0swWPwVs5kcvAGrEdMy35pCOOX9Hcyfi7fT+d1s8tIC1WzrmexXwG0nuAJ4G3lVV067y860sJEmSJEkuK5UkSZIkWRxKkiRJkrA4lCRJkiRhcShJkiRJwuJQkiRJkoTFoSRJkiQJi0NJkvYISe5v3mNw2HFcn+Qtw45DkjR4Y8MOQJIkDV+SABl2HJKk4XHmUJKkPUiSxUluTPKhJI8muTfJCc32DUkeTvKm1vilST6a5LokP0jyz0kOb/WfkGRtki3N5xNafdcneXeSG4FtwDLgRODDSR5L8uFm3KXNc29NckuSE1vHuCjJZ5Nc1Tz/7UmOa/UvSPK5JI8k2TRxzKbvzUnuTLI5yap23JKkwbM4lCRpz/MSYD1wMHA1cA3wYuC5wBvpFW/7tca/AbgEOARYB3wKIMlBwErgsuZYHwRWJjm4te85wNuA/YHFwNeBJVW1X1UtacasBY4BDmriuTbJvNYxFjUxHgisACaKyr2ALwAPAOPAs5pxJDkN+EvgtcBPN8/76Z3/VkmS+sXiUJKkPc99VfWJqnoa+AywALi4qp6oqi8DT9IrFCesrKrVVfUEcD7w0iQLgFcDd1fVsqraXlWfBu4CTm3tu7Sqbm/6n5oqmKr6ZFVtasb8LbAP8LzWkBuq6otNvMuAo5vtxwOHAu+qqv+uqser6oam71zgvVV1Z1VtB94DHOPsoSQNj8WhJEl7noda7f8BqKrJ29ozhxsmGlX1GPB9ekXZofRm7doeoDeD93/23ZEk5zXLP7ckeRSYT2+WcsJ/ttrbgHlJxugVtQ80xd9khwOXNktnH21izqTYJEkDZHEoSdLoWzDRaJabHgT8e/MxeSbuMODB1uOa1P9jj5vrC/8UOAN4RlUdCGyh281rNgCHNYXiVH2/X1UHtj5+qqpu6nBcSdIssDiUJGn0vSrJy5LsTe/awzVVtQH4IrAwyeuTjCU5E3g+vesAd+Qh4Bdaj/cHtgOPAGNJLgQO6BjXvwD/AfxNkn2TzEvyK03fR4G/SHIkQJL5SX6743ElSbPA4lCSpNF3NfBX9JZmHkvvpjVU1SbgFOCdwCZ6M4CnVNV/TXOsS4HTmzuIXgasAr4EfJfektTH6bAUtXn+p+ld3/hc4HvARuDMpu/zwPuAa5JsBW4DfrP7lyxJ6rdUTV5NIkmSRkWSpcDGqrpg2LFIkkabM4eSJEmSJItDSZIkSZLLSiVJkiRJOHMoSZIkScLiUJIkSZKExaEkSZIkCYtDSZIkSRIWh5IkSZIk4H8B1lp5f8xHafgAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LQRJKFuJCSBZ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 496
        },
        "outputId": "c6b45853-057c-4ccb-d13f-8bbc0b963837"
      },
      "source": [
        "model_permutation_importance(best_model)"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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uGuCYJCcB21bVA4N1qqrfAJOTPB34U+BsYC86YW4u8ELgtqr6WXPKl5rj/b4+YMjPA4uq6uTl1HVbVfUHy+uAqc336Z5eVVc27Wd39d8L+EpT6wJgQdexw5tZwXnANsDWVVXAmcAbmnF3A763nFokSZIktdi4DHNVdRmdIPTfwOwkb1xB9yvozGDdwpMzdbsBlw/hUr8bZKx9mhm9wTzctb2MEX5nMcnzgfcAL6uq7YDzgf5rngG8AXg9cG5VPTaSa0iSJEka28ZlmEvyPOCuqjoN+CKw4wq6z6UTjC6jM8u1D/BwVS2hE/CmJtmi6fsXwI9WMNa/A98FzkkypKBWVfcDDyTZtWk6ouvwZXSWjJJkOp0llQAb0gmSS5I8E3h513h3AncCJ9IJdpIkSZLGoXH1NssuewPHJ3kUeBBY0czcXDpLLC+rqmVJ7gBuBqiqh5IcA5zbhLNrgM+t6MJV9fEkU4Azkxw1xHrfDJyW5HE6YXFJ034qcEaSm4Cb6CzNpKpuSDKvqfMO/nAW8Sxg06q6aYjX1wT2Z5uvz0uftx4bHv4xf2NOkiSpRcZVmKuqyc2/X6Lz/bahnHMrkK79AwYcvwjYYZDzpg7Y37tr+/1dh/r73QNM7+rz0a4+NzbLJUlyAnBt02cpT52p677erOXdE7AHcNoKjktP6JsU+iaFKRtv3OtSJEmSNAzjKsy12CuT/D86z+OXwKyRDpTkOjpLMP9m9ZQmSZIkaSyaMGEuydXAegOa/6KqFvainm5V9XX+8M2YIx1r5sp7SZIkSWq7CRPmqmrXlfeSJEmSpHYYl2+zlCRJkqTxzjAnSZIkSS1kmJMkSZKkFjLMSZIkSVILGeYkSZIkqYUmzNss9VRTjv73XpegFVi8eDHTpk3rdRmSJEkaw5yZkyRJkqQWMsxJkiRJUgsZ5iRJkiSphQxzkiRJktRChjlJkiRJaiHDnCRJkiS1kGFOkiRJklrI35mboK76xut7XcKE9OJDv9rrEiRJkjROODMnSZIkSS1kmJMkSZKkFjLMSZIkSVILGeYkSZIkqYUMc5IkSZLUQoY5SZIkSWohw5wkSZIktZBhTpIkSZJayDAnSZIkSS20Tq8LkMa7hx8tHnm0s33fffc90d7X10dfX1+PqpIkSVLbGeakNeyam5ZxxaJlnZ1vH/tE++GHH84RRxzRo6okSZLUdi6zHOeSrN3rGiRJkiStfoa5MSTJPyZ5V9f+yUnemeT4JNckWZDkA13Hv53kuiQ3JnlrV/uDST6W5AZgt1G+DUmSJEmjwDA3tpwOvBEgyVrAEcBvgGnALsAMYGaSvZr+b6qqmcBOwDuSPKNp3wC4uqq2r6ofj+YNSJIkSRodfmduDKmq25Pcm2QH4JnAPGBn4IBmG2AynXB3GZ0A9+qm/U+b9nuBZcB/jGbtkiRJkkaXYW7s+SIwC/gTOjN1LwP+uao+390pyd7AfsBuVfX7JJcC6zeHH6qqZaNVsCRJkqTR5zLLsedbwIF0ZuQuaP7elGQyQJJnJ/ljYArwv02Q2wp4ca8KliRJkjT6nJkbY6rqkSSXAPc3s2s/SPIi4MokAA8CbwC+DxyX5CbgFuCqXtWsFdv5RWuz/Radl4rOPOizT7T7G3OSJElaFYa5MaZ58cmLgcP626rqk8AnB+n+8sHGqKrJa6Y6jcR6k8J6kzrbG2+8cW+LkSRJ0rjhMssxJMnWwM+Bi6pqca/rkSRJkjR2OTM3hlTVT4EX9LoOSZIkSWOfM3OSJEmS1EKGOUmSJElqIcOcJEmSJLWQYU6SJEmSWsgwJ0mSJEktZJiTJEmSpBYyzEmSJElSC/k7cxPUiw/9aq9LkCRJkrQKnJmTJEmSpBYyzEmSJElSCxnmJEmSJKmFDHOSJEmS1EKGOUmSJElqIcOcJEmSJLWQP00wQX3tvMN7XcJqc8Srzul1CZIkSdKoc2ZOkiRJklrIMCdJkiRJLWSYkyRJkqQWMsxJkiRJUgsZ5iRJkiSphQxzkiRJktRChjlJkiRJaiHDnCRJkiS1kGFOkiRJklrIMKfWevTRYunvi/vuu4+lS5f2uhxJkiRpVE2oMJdkoyRv73UdK5PkXUme1us6xrpbFj3Of56zjGOPPZY5c+b0uhxJkiRpVE2oMAdsBPQ8zKVjRZ/9u4Bhhbkk66xaVZIkSZLaZKKFuQ8DmyeZn+SUJMcnuSbJgiQfAEgyNcnNSWYn+VmSs5Lsl+TyJIuT7NL0OynJmUmubNrf0n+RFYx7S5IvA4uAP01yapJrk9zY1e8dwLOAS5Jc0rQ92DX2oUlmN9uzk3wuydXAvyTZPMn3k1yXZG6SrUbhM5UkSZLUAxNtNucEYHpVzUhyAHAosAsQ4LwkewH/BWwBHAa8CbgGOBLYA3gV8PfAIc142wEvBjYA5iU5H5gOTFvOuNOAo6vqKoAk762q+5KsDVyUZLuq+rck7wb2qap7hnBPzwF2r6plSS4CjquqxUl2BT4L7Dvyj0uSJEnSWDXRwly3A5q/ec3+ZDph67+A26pqIUCSG4GLqqqSLASmdo0xp6qWAkubWbRd6IS+5Y37y/4g1zg8yVvpPIfNgK2BBcO8j3ObIDcZ2B04N0n/sfWGOZYkSZKklpjIYS7AP1fV55/SmEwFHu5qerxr/3Ge+pnVgDFrJeP+rmv/+cB7gJ2r6n+bpZPrL6fW7usM7NM/5lrA/VU1YzljSJIkSRpHJtp35h4Ant5sXwC8qZnRIsmzk/zxMMc7OMn6SZ4B7E1nSeZQx92QThBbkuSZwMuXUyfAXUle1Lw05dWDFVJVvwVuS3JYc90k2X6Y9yNJkiSpJSbUzFxV3du8yGQR8D3gbODKZlnig8AbgGXDGHIBcAmwCfDBqroTuDPJi1Y2blXdkGQecDNwB3B51+EvAN9PcmdV7UPnu37fAe4GrqWzdHMwRwGnJjkRmAR8DbhhGPfTKi+cvhabvxAOPuDz9PX19bocSZIkaVRNqDAHUFVHDmj65CDdpnf1n9W1fXv3MWBBVb1xkGt8cmXjDhx7QPungE917X8D+MYg/WYN2L8NOHCwMcejSZPCpEmw8cYb97oUSZIkadRNtGWWkiRJkjQuTLiZudWlqk7qdQ2SJEmSJi5n5iRJkiSphQxzkiRJktRChjlJkiRJaiHDnCRJkiS1kGFOkiRJklrIMCdJkiRJLWSYkyRJkqQW8nfmJqgjXnVOr0uQJEmStAqcmZMkSZKkFjLMSZIkSVILGeYkSZIkqYUMc5IkSZLUQoY5SZIkSWohw5wkSZIktZA/TTBBvevi1622sT6x79dX21iSJEmShsaZOUmSJElqIcOcJEmSJLWQYU6SJEmSWsgwJ0mSJEktZJiTJEmSpBYyzEmSJElSCxnmJEmSJKmFDHOSJEmS1EKGOUmSJElqIcOcJEmSJLWQYU6r5PFHivvuu4+lS5f2uhRJkiRpQjHMaZX8dt7jHHvsscyZM6fXpUiSJEkTimFuDUmyQZLzk9yQZFGS1yWZmeRHSa5LckGSzZq+b0lyTdP3P5I8rWk/rDn3hiSXNW3rJzkjycIk85Ls07TPSvLNJN9PsjjJv/Tu7iVJkiStaYa5NedA4M6q2r6qpgPfBz4FHFpVM4HTgZObvt+sqp2ranvgJuDNTfv7gD9r2l/VtP0VUFW1LfB64EtJ1m+OzQBeB2wLvC7Jn67ZW5QkSZLUK+v0uoBxbCHwsSQfAb4D/C8wHbgwCcDawK+bvtOTfAjYCJgMXNC0Xw7MTnIO8M2mbQ86oZCqujnJL4Etm2MXVdUSgCQ/BZ4H3LHG7lCSJElSzxjm1pCq+lmSHYFXAB8CLgZurKrdBuk+Gzikqm5IMgvYuxnjuCS7Aq8ErksycyWXfbhrexk+X0mSJGnccpnlGpLkWcDvq+orwCnArsCmSXZrjk9Ksk3T/enAr5NMAo7qGmPzqrq6qt4H3A38KTC3v0+SLYHnAreM0m1JkiRJGiOcuVlztgVOSfI48CjwNuAx4N+STKHz2X8CuBH4B+BqOoHtajrhjub8aUCAi4AbgJuBU5MsbMabVVUPN0s3JUmSJE0Qhrk1pKou4MnvvnXba5C+pwKnDtL+mkHOfwg4ZpC+s+ks1+zfP2jo1Y7chjusxcf/8gv09fWNxuUkSZIkNQxzWiVrrRs23njjXpchSZIkTTh+Z06SJEmSWsgwJ0mSJEktZJiTJEmSpBYyzEmSJElSCxnmJEmSJKmFDHOSJEmS1EKGOUmSJElqIcOcJEmSJLWQPxo+QX1i36/3ugRJkiRJq8CZOUmSJElqIcOcJEmSJLWQYU6SJEmSWsgwJ0mSJEktZJiTJEmSpBYyzEmSJElSC/nTBBPUkRd/YUTnnb3vW1dzJZIkSZJGwpk5SZIkSWohw5wkSZIktZBhTpIkSZJayDAnSZIkSS1kmJMkSZKkFjLMSZIkSVILGeYkSZIkqYUMc5IkSZLUQoY5SZIkSWohw5wkSZIktZBhTkNWjzzG0qVLe12GJEmSJAxzrZZkoyRv79rfO8l31tT1Hpt3G3PmzFlTw0uSJEkaBsNcu20EvH2lvSRJkiSNO4a5UZJkapKbk8xO8rMkZyXZL8nlSRYn2SXJxkm+nWRBkquSbNece1KS05NcmuQXSd7RDPthYPMk85Oc0rRNTvKN5lpnJUlPbliSJEnSGrVOrwuYYLYADgPeBFwDHAnsAbwK+HvgDmBeVR2SZF/gy8CM5tytgH2ApwO3JDkVOAGYXlUzoLPMEtgB2Aa4E7gceAnw49G4OUmSJEmjx5m50XVbVS2sqseBG4GLqqqAhcBUOsHuTICquhh4RpINm3PPr6qHq+oe4H+AZy7nGj+pql8115jfjCtJkiRpnDHMja6Hu7Yf79p/nJXPknafu2wF/YfaT5IkSVKLGebGlrnAUfDEksl7quq3K+j/AJ1ll5IkSZImGGdtxpaTgNOTLAB+Dxy9os5VdW/zApVFwPeA89dkcevs8HwOfunBa/ISkiRJkobIMDdKqup2YHrX/qzlHDtkkHNPGrDfPc6RA7pf2nXs/4y44EFk3XXo6+tbnUNKkiRJGiGXWUqSJElSCxnmJEmSJKmFDHOSJEmS1EKGOUmSJElqIcOcJEmSJLWQYU6SJEmSWsgwJ0mSJEktZJiTJEmSpBbyR8MnqLP3fWuvS5AkSZK0CpyZkyRJkqQWMsxJkiRJUgsZ5iRJkiSphQxzkiRJktRChjlJkiRJaiHDnCRJkiS1kD9NMEEddeF3hn3OWfsftAYqkSRJkjQSzsxJkiRJUgsZ5iRJkiSphQxzkiRJktRChjlJkiRJaiHDnCRJkiS1kGFOkiRJklrIMCdJkiRJLWSYkyRJkqQWMsxJkiRJUgsZ5iRJkiSphQxzkiRJktRChrkRSjI1yaI1MO4/JtlvkPa9k3yn2X5VkhOa7UOSbL2665AkSZI0tq3T6wL0VFX1viH0OQ84r9k9BPgO8NM1WZckSZKkscWZuVWzdpLTktyY5AdJ+pJcmmQngCSbJLm92Z6V5NtJLkxye5L/k+TdSeYluSrJxk2/2UkObbYPTHJzkuuB1/RftBnr00l2B14FnJJkfpLNm779/aZ170uSJEkaPwxzq2Ya8Jmq2ga4H3jtSvpPpxPKdgZOBn5fVTsAVwJv7O6YZH3gNODPgZnAnwwcrKquoDNDd3xVzaiqW4ElSWY0XY4BzhjhvUmSJEkawwxzq+a2qprfbF8HTF1J/0uq6oGquhtYAvxn075wkHO3asZfXFUFfGWINX0ROCbJ2sDrgLOHeJ4kSZKkFjHMrZqHu7aX0fkO4mM8+bmuv4L+j3ftP87q+/7ifwAvBw4Crquqe1fTuJIkSZLGEMPc6nc7nWWRAIeuwjg3A1OTbN7sv345/R4Ant6/U1UPARcAp+ISS0mSJGncMsytfh8F3pZkHrDJSAdpQtlbgfObl5j8z3K6fg04vnmRSn/wO4vObN8PRnp9SZIkSWObP00wQlV1O50XmvTvf7Tr8HZd2yc2x2cDs7v6T+3afuJYVc3qav8+ne/ODbx2d//LgYG/M7cHcEZVLRvi7UiSJElqGcPcOJPkW8DmwL69rkWSJEnSmmOYG2eq6tW9rkGSJEnSmud35iRJkiSphfVFriIAABlySURBVAxzkiRJktRChjlJkiRJaiHDnCRJkiS1kGFOkiRJklrIMCdJkiRJLeRPE0xQZ+1/UK9LkCRJkrQKnJmTJEmSpBYyzEmSJElSCxnmJEmSJKmFDHOSJEmS1EKGOUmSJElqIcOcJEmSJLWQYU6SJEmSWsjfmZugjr7w2mH1/9L+O62hSiRJkiSNhDNzkiRJktRChjlJkiRJaiHDnCRJkiS1kGFOkiRJklrIMCdJkiRJLWSYkyRJkqQWMsxJkiRJUgsZ5iRJkiSphQxzkiRJktRChjmtVD3yMEuXLu11GZIkSZK6GOa0Uo/ccDVz5szpdRmSJEmSuqw0zCV5R5Kbkpw1nIGTTE2yaLgFJXmw+fdZSb7RbM9K8unhjjVg3HcledqqjDEakhySZOte1yFJkiRpbBvKzNzbgf2r6qg1XUy3qrqzqg5djUO+CxgTYS7J2is4fAgwrDCXZJ1Vq0iSJElS26wwzCX5HPAC4HtJ3pvk9CQ/STIvycFNn7WTnJLkmiQLkvzlIONs05w3v+kzbWWFLW9mL8krk1yZZJMkBzTb1yc5N8nk5Yz1DuBZwCVJLmnaBj03ye1J/rmp9dokOya5IMmtSY5r+uyd5LIk5ye5Jcnnkqw1hHE/kuR64LAkb2k+sxuS/EeSpyXZHXgVcEpz/c2TXJpkp2aMTZLc3mzPSnJekouBi5JsMNjzkSRJkjQ+rTDMVdVxwJ3APsAGwMVVtUuzf0qSDYA3A0uqamdgZ+AtSZ4/YKjjgE9W1QxgJ+BXIyk2yauBE4BXNE0nAvtV1Y7AtcC7l3Mf/9Z/H1W1T5JNVnLufzW1zgVmA4cCLwY+0NVnF+Cv6cyibQ68Zgjj3ltVO1bV14BvVtXOVbU9cBPw5qq6AjgPOL6qZlTVrSv5SHYEDq2qlwLvZfDnI0mSJGkcGs7yvAOAVyV5T7O/PvDcpn27JP1LIqcA04CfdZ17JfDeJM+hE2IWj6DWfekEwQOq6rdJDqITpC5PArBuc52hePFKzj2v+XchMLmqHgAeSPJwko2aYz+pql8AJPkqsAfw0ErG/XrX9vQkHwI2AiYDFwyx9m4XVtV9zfbyns9NIxhXkiRJ0hg3nDAX4LVVdctTGjup5a+r6oIB7VP7t6vq7CRXA68EvpvkL6vq4mHWeiudJZ9b0pnxCp0w8/phjsMQzn24+ffxru3+/f7PrAacU0MY93dd27OBQ6rqhiSzgL2Xc85jPDmDuv4Kxhv0+UiSJEkan4bz0wQXAH/dhDeS7NDV/rYkk5r2LQcu70vyAuAXzXLHOcB2I6j1l8BrgS8n2Qa4CnhJki2aa2yQZMsVnP8A8PRme7jnDmaXJM9vviv3OuDHwxz36cCvm8+t++Uy3XUC3A7MbLZX9EKY5T2fVbbu9rty8MF+BU+SJEkaS4YT5j4ITAIWJLmx2Qf4IvBT4PrmhSWf5w9n/A4HFiWZD0wHvjySYqvqZjrB51xgQ2AW8NUkC+gsZ9xqBad/Afh+kkuq6u5hnjuYa4BP01nGeBvwrWGO+w/A1cDlwM1d7V8Djm9eYrI58FE6YXkesMkK6lne81llWXc9+vr6VtdwkiRJklaDVA1cLaiVSbI38J6qOqjXtQzHkiVLnnjYR1947bDO/dL+O632erR8ixcvZtq0lb70VT3kM2oHn9PY5zMa+3xG7eBzGvtW9RlNmTIlA9uGMzMnSZIkSRojevJj00meAVw0yKGXVdW9qzj2t4CBP43wdwNf0LIqqupS4NLVNZ4kSZIkDVdPwlwT2GasobFfvSbGlSRJkqSxxGWWkiRJktRChjlJkiRJaiHDnCRJkiS1kGFOkiRJklrIMCdJkiRJLdSTt1mq9/wRcEmSJKndnJmTJEmSpBYyzEmSJElSCxnmJEmSJKmFDHOSJEmS1EKGOUmSJElqIcOcJEmSJLWQP00wQf3Dxb8dUr8P7rvhGq5EkiRJ0kg4MydJkiRJLWSYkyRJkqQWMsxJkiRJUgsZ5iRJkiSphQxzkiRJktRChjlJkiRJaiHDnCRJkiS1kGFOkiRJklrIMCdJkiRJLWSY0wotXbqUpUuX9roMSZIkSQMY5rRCc+bMYc6cOb0uQ5IkSdIA4y7MJZmV5Fld+7cn2WSUrv3dJBs1f29fxbEG3scXk2y96lVKkiRJGg/GXZgDZgHPWlmnoUiyznD6V9Urqup+YCNglcIcA+6jqo6tqp+u4piSJEmSxomeh7kkxyd5R7P9r0kubrb3TXJWkgOSXJnk+iTnJpncHH9fkmuSLEryhXQcCuwEnJVkfpK+5jJ/3Zy/MMlWzfkbJDk9yU+SzEtycNM+K8l5TR0XLafmzZJc1lxjUZI9m/b+WcAPA5s3x09JsneS73Sd/+kks4ZzH0kuTbJTc87rm3tZlOQjXeM+mOTkJDckuSrJM1fTY5IkSZI0xvQ8zAFzgT2b7Z2AyUkmNW0LgBOB/apqR+Ba4N1N309X1c5VNR3oAw6qqm80fY6qqhlV1f/mjnua808F3tO0vRe4uKp2AfYBTkmyQXNsR+DQqnrpcmo+ErigqmYA2wPzBxw/Abi1qeH4ldz/cO6DZunlR4B9gRnAzkkOaQ5vAFxVVdsDlwFvWcm1JUmSJLXUWAhz1wEzk2wIPAxcSSfU7QksBbYGLk8yHzgaeF5z3j5Jrk6ykE6w2WYF1/hm17WmNtsHACc0414KrA88tzl2YVXdt4LxrgGOSXISsG1VPTC0Wx3UcO4DYGfg0qq6u6oeA84C9mqOPQL0zwB236skSZKkcWZY3wlbE6rq0SS30fmO2BV0ZuP2AbYAbqMTrF7ffU6S9YHPAjtV1R1NqFp/BZd5uPl3GU/ec4DXVtUtA8beFfjdSmq+LMlewCuB2Uk+XlVfXsEpj/HU4Lz+CO9jZR6tqmq2u+9VkiRJ0jgzFmbmoLPU8j10lgbOBY4D5gFXAS9JsgU88T23LXky8NzTfIfu0K6xHgCePoRrXkDnu3Rpxt5hqMUmeR5wV1WdBnyRzrLMbgNr+CWwdZL1kmwEvKxpH8l9/AR4aZJNkqwNvB740VBrH66DDz6Ygw8+eE0NL0mSJGmExsrMzVw632G7sqp+l+QhYG5V3d28KOSrSdZr+p5YVT9LchqwCPgNnWWP/WYDn0uyFNhtBdf8IPAJYEGStejMAh40xHr3Bo5P8ijwIPDG7oNVdW+Sy5MsAr5XVccnOaep9zY6QZWqun+491FVv05yAnAJndnF86tqjf0QXF9f38o7SZIkSRp1eXJVnsa7JUuWPPGw/+Hi3w7pnA/uu+Eaq0fLt3jxYqZNm9brMrQCPqN28DmNfT6jsc9n1A4+p7FvVZ/RlClTMrBtrCyzlCRJkiQNw1hZZjkmJdkWOHNA88NVtWsv6pEkSZKkfoa5FaiqhXR+y02SJEmSxhSXWUqSJElSCxnmJEmSJKmFDHOSJEmS1EKGOUmSJElqIcOcJEmSJLWQb7OcoPwxcEmSJKndnJmTJEmSpBYyzEmSJElSCxnmJEmSJKmFDHOSJEmS1EKGOUmSJElqIcOcJEmSJLWQP00wQV3x/UdXeHz3AyeNUiWSJEmSRsKZOUmSJElqIcOcJEmSJLWQYU6SJEmSWsgwJ0mSJEktZJiTJEmSpBYyzEmSJElSCxnmJEmSJKmFDHOSJEmS1EKGOUmSJElqIcOcJEmSJLWQYW4MSHJpkp1W0mdWkk+PVk2SJEmSxjbDnCRJkiS1kGFuBJIcn+Qdzfa/Jrm42d43yVlJDkhyZZLrk5ybZHJzfGaSHyW5LskFSTYbMO5aSWYn+VCzf0ySnyX5CfCSrn5/nuTqJPOS/DDJM5tzFyfZtGusn/fvS5IkSRpfDHMjMxfYs9neCZicZFLTtgA4EdivqnYErgXe3Rz/FHBoVc0ETgdO7hpzHeAsYHFVndgEvQ/QCXF7AFt39f0x8OKq2gH4GvC3VfU48BXgqKbPfsANVXX36r11SZIkSWPBOr0uoKWuA2Ym2RB4GLieTqjbEziPTvC6PAnAusCVwAuB6cCFTfvawK+7xvw8cE5V9Qe8XYFL+8NYkq8DWzbHngN8vQl86wK3Ne2nA3OATwBvAs5YrXctSZIkacwwzI1AVT2a5DZgFnAFndm4fYAt6ASrC6vq9d3nJNkWuLGqdlvOsFcA+yT5WFU9tJISPgV8vKrOS7I3cFJT1x1J7kqyL7ALT87SSZIkSRpnXGY5cnOB9wCXNdvHAfOAq4CXJNkCIMkGSbYEbgE2TbJb0z4pyTZd4/078F3gnCTrAFcDL03yjGaJ5mFdfacA/91sHz2gri/SWW55blUtW213K0mSJGlMMcyN3FxgM+DKqroLeAiY2yyLnAV8NckCOksst6qqR4BDgY8kuQGYD+zePWBVfZxOIDwTuIvOjNuVwOXATV1dTwLOTXIdcM+Aus4DJuMSS0mSJGlcc5nlCFXVRcCkrv0tu7YvBnYe5Jz5wF6DtO/dtf3+rkNnMEgoq6o5dL4bN5jt6bz45OaV3oQkSZKk1jLMjSNJTgDeht+VkyRJksY9l1mOI1X14ap6XlX9uNe1SJIkSVqzDHOSJEmS1EKGOUmSJElqIcOcJEmSJLWQYU6SJEmSWsgwJ0mSJEktZJiTJEmSpBYyzEmSJElSC/mj4RPU7gdO6nUJkiRJklaBM3OSJEmS1EKGOUmSJElqIcOcJEmSJLWQYU6SJEmSWsgwJ0mSJEktZJiTJEmSpBYyzEmSJElSCxnmJEmSJKmFDHOSJEmS1EKGOUmSJElqIcOcJEmSJLWQYU6SJEmSWsgwJ0mSJEktZJiTJEmSpBYyzEmSJElSCxnmJEmSJKmFDHOSJEmS1EKGOUmSJElqIcPcMCT5bpKNhtF/apJFa7KmFVz7wV5cV5IkSdLoWKfXBbRJVb2i1zVIkiRJEjgz9xRJjk/yjmb7X5Nc3Gzvm+SsJLcn2aSZcbspyWlJbkzygyR9Td+ZSW5IcgPwV11jb5PkJ0nmJ1mQZFozzs3N2Dcl+UaSp3WN86Mk1yW5IMlmTfvmSb7ftM9NslXT/vwkVyZZmORDo/zRSZIkSRplhrmnmgvs2WzvBExOMqlpu2xA32nAZ6pqG+B+4LVN+xnAX1fV9gP6Hwd8sqpmNGP/qml/IfDZqnoR8Fvg7c01PwUcWlUzgdOBk5v+X2jGnwm8B/hs0/5J4NSq2hb49Ug/AEmSJEntYJh7quuAmUk2BB4GrqQTvPakE/S63VZV87vOm9p8n26jquoPfmd29b8S+Pskfwc8r6qWNu13VNXlzfZXgD3oBLzpwIVJ5gMnAs9JMhnYHTi3af88sFlz7kuArw5yXUmSJEnjkN+Z61JVjya5DZgFXAEsAPYBtgBuGtD94a7tZUDfSsY+O8nVwCuB7yb5S+AXQA3sCgS4sap26z7QhMz7m9m9QS+zohokSZIkjR/OzP2huXSWL17WbB8HzKuqlQalqrofuD/JHk3TUf3HkrwA+EVV/RswB9iuOfTcJP2h7Ujgx8AtwKb97UkmJdmmqn4L3JbksKY9SfqXc14OHDHwupIkSZLGJ8PcH5pLZ+nilVV1F/AQf7jEckWOAT7TLINMV/vhwKKmfTrw5ab9FuCvktwE/BGd7709AhwKfKR5kcp8OssroRPU3ty03wgc3LS/sxlnIfDs4dywJEmSpPZxmeUAVXURMKlrf8uu7anN5j10All/+0e7tq8Dul9+8rdN+4eBD3dfq1k2+VhVvWGQOuYDew3Sfhtw4HLau5dlnjjY/UmSJEkaH5yZkyRJkqQWcmauh6rqdrpm+CRJkiRpqJyZkyRJkqQWMsxJkiRJUgsZ5iRJkiSphQxzkiRJktRChjlJkiRJaiHDnCRJkiS1kGFOkiRJklrIMCdJkiRJLWSYkyRJkqQWMsxJkiRJUgsZ5iRJkiSphQxzkiRJktRChjlJkiRJaiHDnCRJkiS1kGFOkiRJklrIMCdJkiRJLWSYkyRJkqQWMsxJkiRJUgsZ5iRJkiSphQxzkiRJktRChjlJkiRJaiHDnCRJkiS1kGFOkiRJklrIMCdJkiRJLWSYkyRJkqQWMsxJkiRJUgsZ5lYiyRUjOOfBYfY/Kcl7mu1/TLLfIH32TvKd4dYiSZIkaXxap9cFjHVVtfsoX+99o3k9SZIkSe3kzNxK9M+yJdksyWVJ5idZlGTPlZx3cpIbklyV5JlN29QkFydZkOSiJM8d5LzZSQ5ttg9McnOS64HXdPXZJcmVSeYluSLJC5v2y5LM6Or34yTbr5YPQpIkSdKYYpgbuiOBC6pqBrA9MH8FfTcArqqq7YHLgLc07Z8CvlT1/9u711g56jKO49+fFOkLsCb2BcqtRGmUSw1YL0QUFGOAaBsjwRIuFht5YSR4iVEDQSKJBoyiJOCFi21RRFsNaYIKRjE1QptCCNcgNhCxaMQoVhOCUHh8MVNZDuWcoT2dZc75fpKmszP/3f2dPNnZeXb+s1uLgB8Cl73YAySZC1wJfBB4C7DvyOYHgHdV1ZHABcBX2vVXA8vb+y8E5lbVXS/hb5QkSZI0EDZz3W0CzkpyIXBEVf1nkrFPAduvb7sDWNAuHw1c1y5fCxwzyWO8EXi4qv5YVQX8YGTbPGBNknuBS4HD2vVrgA8k2RP4GLBy6j9LkiRJ0hDZzHVUVeuBdwOPAiuTnDnJ8KfbBgzgGab/2sSLgFuq6nCaM3dz24xPAL8ClgKn0Jz9kyRJkjQD2cx1lOQg4G9VdSVwFXDUTjzMrcCydvk04HeTjH0AWJDk9e3tU0e2zaNpKqGdVjniKprpm5uq6vGdyChJkiRpAGzmujsOuCvJncBHgG/txGOcQzNV827gDODcFxtYVU8CZwM3tl+A8tjI5kuAr7ZZ5ky43x3Av4Hv70Q+SZIkSQPhTxNMoar2bv9fBax6Kfdpl9cCa9vlPwHv3cH4C0eWl48s/5Lm2rmJ428DFo6sOn/7QpLX0TTpN3fJKkmSJGmYPDM3g7TX8W0EzquqZ8edR5IkSdLu45m5XZBkI7DXhNVnVNU948hTVauB1eN4bkmSJEn9spnbBVX19nFnkCRJkjQ7Oc1SkiRJkgbIZk6SJEmSBshmTpIkSZIGyGZOkiRJkgbIZk6SJEmSBshmTpIkSZIGyGZOkiRJkgYoVTXuDOrJ1q1bLbYkSZI0QPPmzcvEdZ6ZkyRJkqQBspmTJEmSpAFymqUkSZIkDZBn5iRJkiRpgGzmJEmSJGmAbOZmqCQnJPlDks1JvrCD7Xsl+XG7fWOSBf2nVIc6fSbJ/UnuTvLrJAeNI+dsNlWNRsZ9OEklWdxnPnWrUZJT2tfSfUmu6zujOu3vDkxyS5I7233eSePIOZsluSbJY0nufZHtSXJZW8O7kxzVd8bZrkONTmtrc0+SW5O8ue+Ms91UNRoZ99Yk25KcvCvPZzM3AyXZA7gcOBE4FDg1yaEThq0AHq+qNwCXAhf3m1Id63QnsLiqFgFrgUv6TTm7dawRSfYBzgU29ptQXWqU5BDgi8A7q+ow4FO9B53lOr6Wzgd+UlVHAsuAK/pNKWAlcMIk208EDmn/nQ18u4dMer6VTF6jh4Fjq+oI4CLge32E0vOsZPIabd8nXgzcvKtPZjM3M70N2FxVD1XVU8D1wNIJY5YCq9rltcDxSV7w2xXaraasU1XdUlVPtDc3APv3nHG26/JaguYN82LgyT7DCehWo48Dl1fV4wBV9VjPGdWtTgW8ql2eB/ylx3wCqmo98M9JhiwFVldjA/DqJK/tJ51g6hpV1a3b93V43DAWHV5HAOcAPwV2+f3IZm5m2g/488jtLe26HY6pqm3AVuA1vaTTdl3qNGoF8IvdmkgTTVmjdprRAVV1Y5/B9H9dXkcLgYVJfp9kQ5JJPzHVbtGlThcCpyfZAvyc5mBHLy8v9X1L4+Vxw8tQkv2ADzFNZ7bnTMeDSNq9kpwOLAaOHXcWPSfJK4BvAMvHHEWTm0MzLew4mk+p1yc5oqr+NdZUmuhUYGVVfT3J0cC1SQ6vqmfHHUwamiTvoWnmjhl3Fr3AN4HPV9Wz0zEpzmZuZnoUOGDk9v7tuh2N2ZJkDs2Uln/0E0+tLnUiyfuA82jmwP+3p2xqTFWjfYDDgd+2O+R9gXVJllTV7b2lnN26vI62ABur6mng4SQP0jR3m/qJKLrVaQXtdSZVdVuSucB8pmEakqZNp/ctjVeSRcBVwIlV5bHdy89i4Pr2uGE+cFKSbVV1w848mNMsZ6ZNwCFJDk7ySpoLyddNGLMO+Gi7fDLwm/IX5Ps2ZZ2SHAl8F1jidT5jMWmNqmprVc2vqgVVtYDm+gQbuX512d/dQHNWjiTzaaZdPtRnSHWq0yPA8QBJ3gTMBf7ea0pNZR1wZvutlu8AtlbVX8cdSs9JciDwM+CMqnpw3Hn0QlV18Mhxw1rgEzvbyIFn5makqtqW5JPATcAewDVVdV+SLwO3V9U64GqaKSybaS7SXDa+xLNTxzp9DdgbWNN+gvNIVS0ZW+hZpmONNEYda3QT8P4k9wPPAJ/z0+p+dazTZ4Erk3ya5stQlvshY7+S/Ijmg4/57bWLXwL2BKiq79Bcy3gSsBl4AjhrPElnrw41uoDmOxCuaI8btlWVP5nTow41mt7ncz8pSZIkScPjNEtJkiRJGiCbOUmSJEkaIJs5SZIkSRogmzlJkiRJGiCbOUmSJEkaIJs5SZIkSRogmzlJkiRJGqD/AcwlTqKV4pY5AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fR2F0ex7CS4I",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 814
        },
        "outputId": "17e60c95-32eb-4c0a-90e5-98f0d8b300d6"
      },
      "source": [
        "model_tree_visualization(best_model)"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<graphviz.files.Source at 0x7f79d0e37b10>"
            ],
            "image/svg+xml": "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Generated by graphviz version 2.40.1 (20161225.0304)\n -->\n<!-- Title: Tree Pages: 1 -->\n<svg width=\"8822pt\" height=\"580pt\"\n viewBox=\"0.00 0.00 8822.00 580.00\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 576)\">\n<title>Tree</title>\n<polygon fill=\"#ffffff\" stroke=\"transparent\" points=\"-4,4 -4,-576 8818,-576 8818,4 -4,4\"/>\n<!-- 0 -->\n<g id=\"node1\" class=\"node\">\n<title>0</title>\n<path fill=\"#f7d7c0\" stroke=\"#000000\" d=\"M4848.5,-572C4848.5,-572 4729.5,-572 4729.5,-572 4723.5,-572 4717.5,-566 4717.5,-560 4717.5,-560 4717.5,-531 4717.5,-531 4717.5,-525 4723.5,-519 4729.5,-519 4729.5,-519 4848.5,-519 4848.5,-519 4854.5,-519 4860.5,-525 4860.5,-531 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font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.6%</text>\n<text text-anchor=\"middle\" x=\"336\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;100.5</text>\n</g>\n<!-- 8&#45;&gt;9 -->\n<g id=\"edge9\" class=\"edge\">\n<title>8&#45;&gt;9</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M397.2032,-73.8139C386.8767,-64.5654 375.3202,-54.2154 365.0544,-45.0212\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"367.2816,-42.3174 357.4973,-38.2531 362.6115,-47.5319 367.2816,-42.3174\"/>\n</g>\n<!-- 10 -->\n<g id=\"node11\" class=\"node\">\n<title>10</title>\n<path fill=\"#fae5d7\" stroke=\"#000000\" d=\"M522,-38C522,-38 426,-38 426,-38 420,-38 414,-32 414,-26 414,-26 414,-12 414,-12 414,-6 420,0 426,0 426,0 522,0 522,0 528,0 534,-6 534,-12 534,-12 534,-26 534,-26 534,-32 528,-38 522,-38\"/>\n<text text-anchor=\"middle\" x=\"474\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" 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fill=\"#000000\">month &lt;= 4.5</text>\n<text text-anchor=\"middle\" x=\"745\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 2.7%</text>\n<text text-anchor=\"middle\" x=\"745\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;155.4</text>\n</g>\n<!-- 11&#45;&gt;12 -->\n<g id=\"edge12\" class=\"edge\">\n<title>11&#45;&gt;12</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M796.7976,-162.7971C789.5536,-154.0847 781.4036,-144.2826 773.7498,-135.0775\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"776.2714,-132.6357 767.1868,-127.1841 770.8889,-137.1111 776.2714,-132.6357\"/>\n</g>\n<!-- 15 -->\n<g id=\"node16\" class=\"node\">\n<title>15</title>\n<path fill=\"#fefcfa\" stroke=\"#000000\" d=\"M950.5,-127C950.5,-127 835.5,-127 835.5,-127 829.5,-127 823.5,-121 823.5,-115 823.5,-115 823.5,-86 823.5,-86 823.5,-80 829.5,-74 835.5,-74 835.5,-74 950.5,-74 950.5,-74 956.5,-74 962.5,-80 962.5,-86 962.5,-86 962.5,-115 962.5,-115 962.5,-121 956.5,-127 950.5,-127\"/>\n<text text-anchor=\"middle\" x=\"893\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">temperature &lt;= 0.4</text>\n<text text-anchor=\"middle\" x=\"893\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 2.9%</text>\n<text text-anchor=\"middle\" x=\"893\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;174.4</text>\n</g>\n<!-- 11&#45;&gt;15 -->\n<g id=\"edge15\" class=\"edge\">\n<title>11&#45;&gt;15</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M841.2024,-162.7971C848.4464,-154.0847 856.5964,-144.2826 864.2502,-135.0775\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"867.1111,-137.1111 870.8132,-127.1841 861.7286,-132.6357 867.1111,-137.1111\"/>\n</g>\n<!-- 13 -->\n<g id=\"node14\" class=\"node\">\n<title>13</title>\n<path fill=\"#fefbf9\" stroke=\"#000000\" d=\"M660,-38C660,-38 564,-38 564,-38 558,-38 552,-32 552,-26 552,-26 552,-12 552,-12 552,-6 558,0 564,0 564,0 660,0 660,0 666,0 672,-6 672,-12 672,-12 672,-26 672,-26 672,-32 666,-38 660,-38\"/>\n<text text-anchor=\"middle\" x=\"612\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.9%</text>\n<text text-anchor=\"middle\" x=\"612\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;169.9</text>\n</g>\n<!-- 12&#45;&gt;13 -->\n<g id=\"edge13\" class=\"edge\">\n<title>12&#45;&gt;13</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M701.4508,-73.8139C685.6185,-64.1121 667.8078,-53.198 652.2716,-43.6777\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"653.7743,-40.4937 643.4191,-38.2531 650.1169,-46.4623 653.7743,-40.4937\"/>\n</g>\n<!-- 14 -->\n<g id=\"node15\" class=\"node\">\n<title>14</title>\n<path fill=\"#fdf6f1\" stroke=\"#000000\" d=\"M798,-38C798,-38 702,-38 702,-38 696,-38 690,-32 690,-26 690,-26 690,-12 690,-12 690,-6 696,0 702,0 702,0 798,0 798,0 804,0 810,-6 810,-12 810,-12 810,-26 810,-26 810,-32 804,-38 798,-38\"/>\n<text text-anchor=\"middle\" x=\"750\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1.8%</text>\n<text text-anchor=\"middle\" x=\"750\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;148.5</text>\n</g>\n<!-- 12&#45;&gt;14 -->\n<g id=\"edge14\" class=\"edge\">\n<title>12&#45;&gt;14</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M746.6372,-73.8139C747.1378,-65.6535 747.6911,-56.6354 748.2018,-48.3105\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"751.6998,-48.4487 748.8188,-38.2531 744.713,-48.0199 751.6998,-48.4487\"/>\n</g>\n<!-- 16 -->\n<g id=\"node17\" class=\"node\">\n<title>16</title>\n<path fill=\"#fffdfd\" stroke=\"#000000\" d=\"M936,-38C936,-38 840,-38 840,-38 834,-38 828,-32 828,-26 828,-26 828,-12 828,-12 828,-6 834,0 840,0 840,0 936,0 936,0 942,0 948,-6 948,-12 948,-12 948,-26 948,-26 948,-32 942,-38 936,-38\"/>\n<text text-anchor=\"middle\" x=\"888\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.9%</text>\n<text text-anchor=\"middle\" x=\"888\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;181.9</text>\n</g>\n<!-- 15&#45;&gt;16 -->\n<g id=\"edge16\" class=\"edge\">\n<title>15&#45;&gt;16</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M891.3628,-73.8139C890.8622,-65.6535 890.3089,-56.6354 889.7982,-48.3105\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"893.287,-48.0199 889.1812,-38.2531 886.3002,-48.4487 893.287,-48.0199\"/>\n</g>\n<!-- 17 -->\n<g id=\"node18\" class=\"node\">\n<title>17</title>\n<path fill=\"#fefbf9\" stroke=\"#000000\" d=\"M1074,-38C1074,-38 978,-38 978,-38 972,-38 966,-32 966,-26 966,-26 966,-12 966,-12 966,-6 972,0 978,0 978,0 1074,0 1074,0 1080,0 1086,-6 1086,-12 1086,-12 1086,-26 1086,-26 1086,-32 1080,-38 1074,-38\"/>\n<text text-anchor=\"middle\" x=\"1026\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1.9%</text>\n<text text-anchor=\"middle\" x=\"1026\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;170.8</text>\n</g>\n<!-- 15&#45;&gt;17 -->\n<g id=\"edge17\" class=\"edge\">\n<title>15&#45;&gt;17</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M936.5492,-73.8139C952.3815,-64.1121 970.1922,-53.198 985.7284,-43.6777\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"987.8831,-46.4623 994.5809,-38.2531 984.2257,-40.4937 987.8831,-46.4623\"/>\n</g>\n<!-- 19 -->\n<g id=\"node20\" class=\"node\">\n<title>19</title>\n<path fill=\"#fefaf8\" stroke=\"#000000\" d=\"M1596.5,-216C1596.5,-216 1477.5,-216 1477.5,-216 1471.5,-216 1465.5,-210 1465.5,-204 1465.5,-204 1465.5,-175 1465.5,-175 1465.5,-169 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class=\"edge\">\n<title>18&#45;&gt;26</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1716.003,-251.7971C1725.0802,-242.8207 1735.3272,-232.6876 1744.8786,-223.2423\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1747.3666,-225.7042 1752.0161,-216.1841 1742.4446,-220.7269 1747.3666,-225.7042\"/>\n</g>\n<!-- 20 -->\n<g id=\"node21\" class=\"node\">\n<title>20</title>\n<path fill=\"#fdf4ee\" stroke=\"#000000\" d=\"M1394,-127C1394,-127 1210,-127 1210,-127 1204,-127 1198,-121 1198,-115 1198,-115 1198,-86 1198,-86 1198,-80 1204,-74 1210,-74 1210,-74 1394,-74 1394,-74 1400,-74 1406,-80 1406,-86 1406,-86 1406,-115 1406,-115 1406,-121 1400,-127 1394,-127\"/>\n<text text-anchor=\"middle\" x=\"1302\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">feels_like_temperature &lt;= 0.3</text>\n<text text-anchor=\"middle\" x=\"1302\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1.3%</text>\n<text text-anchor=\"middle\" x=\"1302\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;137.6</text>\n</g>\n<!-- 19&#45;&gt;20 -->\n<g id=\"edge20\" class=\"edge\">\n<title>19&#45;&gt;20</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1466.8106,-162.9176C1440.0734,-152.7916 1409.4126,-141.1797 1381.8443,-130.7389\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1382.825,-127.3678 1372.2336,-127.0991 1380.3457,-133.914 1382.825,-127.3678\"/>\n</g>\n<!-- 23 -->\n<g id=\"node24\" class=\"node\">\n<title>23</title>\n<path fill=\"#fefcfb\" stroke=\"#000000\" d=\"M1596.5,-127C1596.5,-127 1477.5,-127 1477.5,-127 1471.5,-127 1465.5,-121 1465.5,-115 1465.5,-115 1465.5,-86 1465.5,-86 1465.5,-80 1471.5,-74 1477.5,-74 1477.5,-74 1596.5,-74 1596.5,-74 1602.5,-74 1608.5,-80 1608.5,-86 1608.5,-86 1608.5,-115 1608.5,-115 1608.5,-121 1602.5,-127 1596.5,-127\"/>\n<text text-anchor=\"middle\" x=\"1537\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">hour_of_day &lt;= 3.5</text>\n<text text-anchor=\"middle\" x=\"1537\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 4.0%</text>\n<text text-anchor=\"middle\" x=\"1537\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;176.9</text>\n</g>\n<!-- 19&#45;&gt;23 -->\n<g id=\"edge23\" class=\"edge\">\n<title>19&#45;&gt;23</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1537,-162.7971C1537,-154.7887 1537,-145.8597 1537,-137.3198\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1540.5001,-137.1841 1537,-127.1841 1533.5001,-137.1841 1540.5001,-137.1841\"/>\n</g>\n<!-- 21 -->\n<g id=\"node22\" class=\"node\">\n<title>21</title>\n<path fill=\"#fef9f5\" stroke=\"#000000\" d=\"M1212,-38C1212,-38 1116,-38 1116,-38 1110,-38 1104,-32 1104,-26 1104,-26 1104,-12 1104,-12 1104,-6 1110,0 1116,0 1116,0 1212,0 1212,0 1218,0 1224,-6 1224,-12 1224,-12 1224,-26 1224,-26 1224,-32 1218,-38 1212,-38\"/>\n<text text-anchor=\"middle\" x=\"1164\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.5%</text>\n<text text-anchor=\"middle\" x=\"1164\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;159.5</text>\n</g>\n<!-- 20&#45;&gt;21 -->\n<g id=\"edge21\" class=\"edge\">\n<title>20&#45;&gt;21</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1256.8136,-73.8139C1240.2325,-64.0214 1221.5603,-52.9939 1205.3342,-43.4112\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1206.9906,-40.3246 1196.6003,-38.2531 1203.431,-46.352 1206.9906,-40.3246\"/>\n</g>\n<!-- 22 -->\n<g id=\"node23\" class=\"node\">\n<title>22</title>\n<path fill=\"#fcf1e9\" stroke=\"#000000\" d=\"M1350,-38C1350,-38 1254,-38 1254,-38 1248,-38 1242,-32 1242,-26 1242,-26 1242,-12 1242,-12 1242,-6 1248,0 1254,0 1254,0 1350,0 1350,0 1356,0 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1500,-26 1500,-32 1494,-38 1488,-38\"/>\n<text text-anchor=\"middle\" x=\"1440\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1.3%</text>\n<text text-anchor=\"middle\" x=\"1440\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;165.3</text>\n</g>\n<!-- 23&#45;&gt;24 -->\n<g id=\"edge24\" class=\"edge\">\n<title>23&#45;&gt;24</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1505.2386,-73.8139C1494.1233,-64.4747 1481.6711,-54.0123 1470.6486,-44.7511\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1472.8225,-42.0062 1462.9147,-38.2531 1468.3195,-47.3656 1472.8225,-42.0062\"/>\n</g>\n<!-- 25 -->\n<g id=\"node26\" class=\"node\">\n<title>25</title>\n<path fill=\"#fffefd\" stroke=\"#000000\" d=\"M1626,-38C1626,-38 1530,-38 1530,-38 1524,-38 1518,-32 1518,-26 1518,-26 1518,-12 1518,-12 1518,-6 1524,0 1530,0 1530,0 1626,0 1626,0 1632,0 1638,-6 1638,-12 1638,-12 1638,-26 1638,-26 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1850.5,-80 1850.5,-86 1850.5,-86 1850.5,-115 1850.5,-115 1850.5,-121 1844.5,-127 1838.5,-127\"/>\n<text text-anchor=\"middle\" x=\"1779\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">hour_of_day &lt;= 2.5</text>\n<text text-anchor=\"middle\" x=\"1779\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 8.1%</text>\n<text text-anchor=\"middle\" x=\"1779\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;184.7</text>\n</g>\n<!-- 26&#45;&gt;27 -->\n<g id=\"edge27\" class=\"edge\">\n<title>26&#45;&gt;27</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M1779,-162.7971C1779,-154.7887 1779,-145.8597 1779,-137.3198\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"1782.5001,-137.1841 1779,-127.1841 1775.5001,-137.1841 1782.5001,-137.1841\"/>\n</g>\n<!-- 30 -->\n<g id=\"node31\" class=\"node\">\n<title>30</title>\n<path fill=\"#fefaf7\" 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stroke=\"#000000\" d=\"M3225.8401,-342.7085C3185.0229,-329.594 3135.2983,-313.6175 3095.6611,-300.8821\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"3096.6642,-297.5282 3086.0729,-297.8014 3094.5229,-304.1927 3096.6642,-297.5282\"/>\n</g>\n<!-- 49 -->\n<g id=\"node50\" class=\"node\">\n<title>49</title>\n<path fill=\"#fbeadd\" stroke=\"#000000\" d=\"M3636.5,-305C3636.5,-305 3521.5,-305 3521.5,-305 3515.5,-305 3509.5,-299 3509.5,-293 3509.5,-293 3509.5,-264 3509.5,-264 3509.5,-258 3515.5,-252 3521.5,-252 3521.5,-252 3636.5,-252 3636.5,-252 3642.5,-252 3648.5,-258 3648.5,-264 3648.5,-264 3648.5,-293 3648.5,-293 3648.5,-299 3642.5,-305 3636.5,-305\"/>\n<text text-anchor=\"middle\" x=\"3579\" y=\"-289.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">temperature &lt;= 0.4</text>\n<text text-anchor=\"middle\" x=\"3579\" y=\"-274.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 2.8%</text>\n<text text-anchor=\"middle\" x=\"3579\" y=\"-259.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;88.5</text>\n</g>\n<!-- 33&#45;&gt;49 -->\n<g id=\"edge49\" class=\"edge\">\n<title>33&#45;&gt;49</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M3380.2484,-342.5902C3417.4319,-330.5998 3461.9675,-316.2387 3499.4474,-304.1528\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"3500.8727,-307.3708 3509.3159,-300.9706 3498.7243,-300.7086 3500.8727,-307.3708\"/>\n</g>\n<!-- 35 -->\n<g id=\"node36\" class=\"node\">\n<title>35</title>\n<path fill=\"#fffefe\" stroke=\"#000000\" d=\"M2661,-216C2661,-216 2565,-216 2565,-216 2559,-216 2553,-210 2553,-204 2553,-204 2553,-175 2553,-175 2553,-169 2559,-163 2565,-163 2565,-163 2661,-163 2661,-163 2667,-163 2673,-169 2673,-175 2673,-175 2673,-204 2673,-204 2673,-210 2667,-216 2661,-216\"/>\n<text text-anchor=\"middle\" x=\"2613\" y=\"-200.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">year &lt;= 0.5</text>\n<text text-anchor=\"middle\" x=\"2613\" y=\"-185.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.4%</text>\n<text text-anchor=\"middle\" x=\"2613\" y=\"-170.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;185.5</text>\n</g>\n<!-- 34&#45;&gt;35 -->\n<g id=\"edge35\" class=\"edge\">\n<title>34&#45;&gt;35</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M2965.9463,-265.5586C2890.8559,-249.3769 2762.5376,-221.7248 2683.0494,-204.5954\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"2683.6392,-201.1422 2673.1262,-202.457 2682.1645,-207.9851 2683.6392,-201.1422\"/>\n</g>\n<!-- 42 -->\n<g id=\"node43\" class=\"node\">\n<title>42</title>\n<path fill=\"#fefaf8\" stroke=\"#000000\" d=\"M3074,-216C3074,-216 2978,-216 2978,-216 2972,-216 2966,-210 2966,-204 2966,-204 2966,-175 2966,-175 2966,-169 2972,-163 2978,-163 2978,-163 3074,-163 3074,-163 3080,-163 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stroke=\"#000000\" d=\"M2613,-162.7971C2613,-154.7887 2613,-145.8597 2613,-137.3198\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"2616.5001,-137.1841 2613,-127.1841 2609.5001,-137.1841 2616.5001,-137.1841\"/>\n</g>\n<!-- 37 -->\n<g id=\"node38\" class=\"node\">\n<title>37</title>\n<path fill=\"#ffffff\" stroke=\"#000000\" d=\"M2316,-38C2316,-38 2220,-38 2220,-38 2214,-38 2208,-32 2208,-26 2208,-26 2208,-12 2208,-12 2208,-6 2214,0 2220,0 2220,0 2316,0 2316,0 2322,0 2328,-6 2328,-12 2328,-12 2328,-26 2328,-26 2328,-32 2322,-38 2316,-38\"/>\n<text text-anchor=\"middle\" x=\"2268\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.1%</text>\n<text text-anchor=\"middle\" x=\"2268\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;189.2</text>\n</g>\n<!-- 36&#45;&gt;37 -->\n<g id=\"edge37\" class=\"edge\">\n<title>36&#45;&gt;37</title>\n<path fill=\"none\" stroke=\"#000000\" 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font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.0%</text>\n<text text-anchor=\"middle\" x=\"2820\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;145.2</text>\n</g>\n<!-- 43&#45;&gt;44 -->\n<g id=\"edge44\" class=\"edge\">\n<title>43&#45;&gt;44</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M2911.4685,-73.8139C2895.1277,-64.0214 2876.7261,-52.9939 2860.7352,-43.4112\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"2862.5047,-40.3912 2852.1278,-38.2531 2858.9064,-46.3956 2862.5047,-40.3912\"/>\n</g>\n<!-- 45 -->\n<g id=\"node46\" class=\"node\">\n<title>45</title>\n<path fill=\"#fefcfa\" stroke=\"#000000\" d=\"M3006,-38C3006,-38 2910,-38 2910,-38 2904,-38 2898,-32 2898,-26 2898,-26 2898,-12 2898,-12 2898,-6 2904,0 2910,0 2910,0 3006,0 3006,0 3012,0 3018,-6 3018,-12 3018,-12 3018,-26 3018,-26 3018,-32 3012,-38 3006,-38\"/>\n<text text-anchor=\"middle\" x=\"2958\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.5%</text>\n<text text-anchor=\"middle\" x=\"2958\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;174.4</text>\n</g>\n<!-- 43&#45;&gt;45 -->\n<g id=\"edge45\" class=\"edge\">\n<title>43&#45;&gt;45</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M2956.6549,-73.8139C2956.8551,-65.6535 2957.0764,-56.6354 2957.2807,-48.3105\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"2960.7811,-48.336 2957.5275,-38.2531 2953.7832,-48.1642 2960.7811,-48.336\"/>\n</g>\n<!-- 47 -->\n<g id=\"node48\" class=\"node\">\n<title>47</title>\n<path fill=\"#fef9f6\" stroke=\"#000000\" d=\"M3144,-38C3144,-38 3048,-38 3048,-38 3042,-38 3036,-32 3036,-26 3036,-26 3036,-12 3036,-12 3036,-6 3042,0 3048,0 3048,0 3144,0 3144,0 3150,0 3156,-6 3156,-12 3156,-12 3156,-26 3156,-26 3156,-32 3150,-38 3144,-38\"/>\n<text text-anchor=\"middle\" x=\"3096\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.4%</text>\n<text text-anchor=\"middle\" x=\"3096\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;162.9</text>\n</g>\n<!-- 46&#45;&gt;47 -->\n<g id=\"edge47\" class=\"edge\">\n<title>46&#45;&gt;47</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M3096.6726,-73.8139C3096.5724,-65.6535 3096.4618,-56.6354 3096.3596,-48.3105\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"3099.8588,-48.2093 3096.2362,-38.2531 3092.8593,-48.2953 3099.8588,-48.2093\"/>\n</g>\n<!-- 48 -->\n<g id=\"node49\" class=\"node\">\n<title>48</title>\n<path fill=\"#fdf4ed\" stroke=\"#000000\" d=\"M3282,-38C3282,-38 3186,-38 3186,-38 3180,-38 3174,-32 3174,-26 3174,-26 3174,-12 3174,-12 3174,-6 3180,0 3186,0 3186,0 3282,0 3282,0 3288,0 3294,-6 3294,-12 3294,-12 3294,-26 3294,-26 3294,-32 3288,-38 3282,-38\"/>\n<text text-anchor=\"middle\" x=\"3234\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.0%</text>\n<text text-anchor=\"middle\" x=\"3234\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;136.7</text>\n</g>\n<!-- 46&#45;&gt;48 -->\n<g id=\"edge48\" class=\"edge\">\n<title>46&#45;&gt;48</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M3141.8589,-73.8139C3158.3199,-64.0214 3176.8568,-52.9939 3192.9653,-43.4112\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"3194.8311,-46.3737 3201.636,-38.2531 3191.2523,-40.3578 3194.8311,-46.3737\"/>\n</g>\n<!-- 50 -->\n<g id=\"node51\" class=\"node\">\n<title>50</title>\n<path fill=\"#fcf0e8\" stroke=\"#000000\" d=\"M3627,-216C3627,-216 3531,-216 3531,-216 3525,-216 3519,-210 3519,-204 3519,-204 3519,-175 3519,-175 3519,-169 3525,-163 3531,-163 3531,-163 3627,-163 3627,-163 3633,-163 3639,-169 3639,-175 3639,-175 3639,-204 3639,-204 3639,-210 3633,-216 3627,-216\"/>\n<text text-anchor=\"middle\" x=\"3579\" y=\"-200.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">year &lt;= 0.5</text>\n<text text-anchor=\"middle\" x=\"3579\" y=\"-185.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1.2%</text>\n<text text-anchor=\"middle\" x=\"3579\" y=\"-170.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;119.7</text>\n</g>\n<!-- 49&#45;&gt;50 -->\n<g id=\"edge50\" class=\"edge\">\n<title>49&#45;&gt;50</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M3579,-251.7971C3579,-243.7887 3579,-234.8597 3579,-226.3198\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"3582.5001,-226.1841 3579,-216.1841 3575.5001,-226.1841 3582.5001,-226.1841\"/>\n</g>\n<!-- 57 -->\n<g id=\"node58\" class=\"node\">\n<title>57</title>\n<path fill=\"#fae4d5\" stroke=\"#000000\" d=\"M4027,-216C4027,-216 3931,-216 3931,-216 3925,-216 3919,-210 3919,-204 3919,-204 3919,-175 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51&#45;&gt;52 -->\n<g id=\"edge52\" class=\"edge\">\n<title>51&#45;&gt;52</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M3464.8136,-73.8139C3448.2325,-64.0214 3429.5603,-52.9939 3413.3342,-43.4112\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"3414.9906,-40.3246 3404.6003,-38.2531 3411.431,-46.352 3414.9906,-40.3246\"/>\n</g>\n<!-- 53 -->\n<g id=\"node54\" class=\"node\">\n<title>53</title>\n<path fill=\"#fbede3\" stroke=\"#000000\" d=\"M3558,-38C3558,-38 3462,-38 3462,-38 3456,-38 3450,-32 3450,-26 3450,-26 3450,-12 3450,-12 3450,-6 3456,0 3462,0 3462,0 3558,0 3558,0 3564,0 3570,-6 3570,-12 3570,-12 3570,-26 3570,-26 3570,-32 3564,-38 3558,-38\"/>\n<text text-anchor=\"middle\" x=\"3510\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.2%</text>\n<text text-anchor=\"middle\" x=\"3510\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;104.7</text>\n</g>\n<!-- 51&#45;&gt;53 -->\n<g id=\"edge53\" class=\"edge\">\n<title>51&#45;&gt;53</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M3510,-73.8139C3510,-65.6535 3510,-56.6354 3510,-48.3105\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"3513.5001,-48.253 3510,-38.2531 3506.5001,-48.2531 3513.5001,-48.253\"/>\n</g>\n<!-- 55 -->\n<g id=\"node56\" class=\"node\">\n<title>55</title>\n<path fill=\"#fcefe6\" stroke=\"#000000\" d=\"M3696,-38C3696,-38 3600,-38 3600,-38 3594,-38 3588,-32 3588,-26 3588,-26 3588,-12 3588,-12 3588,-6 3594,0 3600,0 3600,0 3696,0 3696,0 3702,0 3708,-6 3708,-12 3708,-12 3708,-26 3708,-26 3708,-32 3702,-38 3696,-38\"/>\n<text text-anchor=\"middle\" x=\"3648\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.3%</text>\n<text text-anchor=\"middle\" x=\"3648\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;113.3</text>\n</g>\n<!-- 54&#45;&gt;55 -->\n<g id=\"edge55\" class=\"edge\">\n<title>54&#45;&gt;55</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M3648,-73.8139C3648,-65.6535 3648,-56.6354 3648,-48.3105\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"3651.5001,-48.253 3648,-38.2531 3644.5001,-48.2531 3651.5001,-48.253\"/>\n</g>\n<!-- 56 -->\n<g id=\"node57\" class=\"node\">\n<title>56</title>\n<path fill=\"#fae7d9\" stroke=\"#000000\" d=\"M3834,-38C3834,-38 3738,-38 3738,-38 3732,-38 3726,-32 3726,-26 3726,-26 3726,-12 3726,-12 3726,-6 3732,0 3738,0 3738,0 3834,0 3834,0 3840,0 3846,-6 3846,-12 3846,-12 3846,-26 3846,-26 3846,-32 3840,-38 3834,-38\"/>\n<text text-anchor=\"middle\" x=\"3786\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.3%</text>\n<text text-anchor=\"middle\" x=\"3786\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;74.9</text>\n</g>\n<!-- 54&#45;&gt;56 -->\n<g id=\"edge56\" class=\"edge\">\n<title>54&#45;&gt;56</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M3693.1864,-73.8139C3709.7675,-64.0214 3728.4397,-52.9939 3744.6658,-43.4112\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"3746.569,-46.352 3753.3997,-38.2531 3743.0094,-40.3246 3746.569,-46.352\"/>\n</g>\n<!-- 58 -->\n<g id=\"node59\" class=\"node\">\n<title>58</title>\n<path fill=\"#fbeadf\" stroke=\"#000000\" d=\"M4027,-127C4027,-127 3931,-127 3931,-127 3925,-127 3919,-121 3919,-115 3919,-115 3919,-86 3919,-86 3919,-80 3925,-74 3931,-74 3931,-74 4027,-74 4027,-74 4033,-74 4039,-80 4039,-86 4039,-86 4039,-115 4039,-115 4039,-121 4033,-127 4027,-127\"/>\n<text text-anchor=\"middle\" x=\"3979\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">month &lt;= 4.5</text>\n<text text-anchor=\"middle\" x=\"3979\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.7%</text>\n<text text-anchor=\"middle\" x=\"3979\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;92.8</text>\n</g>\n<!-- 57&#45;&gt;58 -->\n<g id=\"edge58\" class=\"edge\">\n<title>57&#45;&gt;58</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M3979,-162.7971C3979,-154.7887 3979,-145.8597 3979,-137.3198\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"3982.5001,-137.1841 3979,-127.1841 3975.5001,-137.1841 3982.5001,-137.1841\"/>\n</g>\n<!-- 61 -->\n<g id=\"node62\" class=\"node\">\n<title>61</title>\n<path fill=\"#f8dfcd\" stroke=\"#000000\" d=\"M4275.5,-127C4275.5,-127 4124.5,-127 4124.5,-127 4118.5,-127 4112.5,-121 4112.5,-115 4112.5,-115 4112.5,-86 4112.5,-86 4112.5,-80 4118.5,-74 4124.5,-74 4124.5,-74 4275.5,-74 4275.5,-74 4281.5,-74 4287.5,-80 4287.5,-86 4287.5,-86 4287.5,-115 4287.5,-115 4287.5,-121 4281.5,-127 4275.5,-127\"/>\n<text text-anchor=\"middle\" x=\"4200\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">weather_situation &lt;= 2.5</text>\n<text text-anchor=\"middle\" x=\"4200\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.8%</text>\n<text text-anchor=\"middle\" x=\"4200\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;38.8</text>\n</g>\n<!-- 57&#45;&gt;61 -->\n<g id=\"edge61\" class=\"edge\">\n<title>57&#45;&gt;61</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M4039.0973,-165.2979C4065.5096,-154.6613 4096.8114,-142.0556 4124.7537,-130.8028\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"4126.1205,-134.0256 4134.089,-127.0433 4123.5055,-127.5324 4126.1205,-134.0256\"/>\n</g>\n<!-- 59 -->\n<g id=\"node60\" class=\"node\">\n<title>59</title>\n<path fill=\"#fcf1e9\" stroke=\"#000000\" d=\"M3972,-38C3972,-38 3876,-38 3876,-38 3870,-38 3864,-32 3864,-26 3864,-26 3864,-12 3864,-12 3864,-6 3870,0 3876,0 3876,0 3972,0 3972,0 3978,0 3984,-6 3984,-12 3984,-12 3984,-26 3984,-26 3984,-32 3978,-38 3972,-38\"/>\n<text text-anchor=\"middle\" x=\"3924\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.1%</text>\n<text text-anchor=\"middle\" x=\"3924\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;123.2</text>\n</g>\n<!-- 58&#45;&gt;59 -->\n<g id=\"edge59\" class=\"edge\">\n<title>58&#45;&gt;59</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M3960.9909,-73.8139C3955.1168,-65.1094 3948.5841,-55.4292 3942.6631,-46.6553\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"3945.4879,-44.5843 3936.9929,-38.2531 3939.6856,-48.5 3945.4879,-44.5843\"/>\n</g>\n<!-- 60 -->\n<g id=\"node61\" class=\"node\">\n<title>60</title>\n<path fill=\"#fbeade\" stroke=\"#000000\" d=\"M4110,-38C4110,-38 4014,-38 4014,-38 4008,-38 4002,-32 4002,-26 4002,-26 4002,-12 4002,-12 4002,-6 4008,0 4014,0 4014,0 4110,0 4110,0 4116,0 4122,-6 4122,-12 4122,-12 4122,-26 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4260,-32 4254,-38 4248,-38\"/>\n<text text-anchor=\"middle\" x=\"4200\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.7%</text>\n<text text-anchor=\"middle\" x=\"4200\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;32.8</text>\n</g>\n<!-- 61&#45;&gt;62 -->\n<g id=\"edge62\" class=\"edge\">\n<title>61&#45;&gt;62</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M4200,-73.8139C4200,-65.6535 4200,-56.6354 4200,-48.3105\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"4203.5001,-48.253 4200,-38.2531 4196.5001,-48.2531 4203.5001,-48.253\"/>\n</g>\n<!-- 63 -->\n<g id=\"node64\" class=\"node\">\n<title>63</title>\n<path fill=\"#fbeadf\" stroke=\"#000000\" d=\"M4386,-38C4386,-38 4290,-38 4290,-38 4284,-38 4278,-32 4278,-26 4278,-26 4278,-12 4278,-12 4278,-6 4284,0 4290,0 4290,0 4386,0 4386,0 4392,0 4398,-6 4398,-12 4398,-12 4398,-26 4398,-26 4398,-32 4392,-38 4386,-38\"/>\n<text text-anchor=\"middle\" x=\"4338\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.1%</text>\n<text text-anchor=\"middle\" x=\"4338\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;92.6</text>\n</g>\n<!-- 61&#45;&gt;63 -->\n<g id=\"edge63\" class=\"edge\">\n<title>61&#45;&gt;63</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M4245.1864,-73.8139C4261.7675,-64.0214 4280.4397,-52.9939 4296.6658,-43.4112\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"4298.569,-46.352 4305.3997,-38.2531 4295.0094,-40.3246 4298.569,-46.352\"/>\n</g>\n<!-- 65 -->\n<g id=\"node66\" class=\"node\">\n<title>65</title>\n<path fill=\"#f7d9c4\" stroke=\"#000000\" d=\"M5448,-394C5448,-394 5344,-394 5344,-394 5338,-394 5332,-388 5332,-382 5332,-382 5332,-353 5332,-353 5332,-347 5338,-341 5344,-341 5344,-341 5448,-341 5448,-341 5454,-341 5460,-347 5460,-353 5460,-353 5460,-382 5460,-382 5460,-388 5454,-394 5448,-394\"/>\n<text text-anchor=\"middle\" x=\"5396\" y=\"-378.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">year &lt;= 0.5</text>\n<text text-anchor=\"middle\" x=\"5396\" y=\"-363.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 31.9%</text>\n<text text-anchor=\"middle\" x=\"5396\" y=\"-348.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;13.1</text>\n</g>\n<!-- 64&#45;&gt;65 -->\n<g id=\"edge65\" class=\"edge\">\n<title>64&#45;&gt;65</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5396,-429.7971C5396,-421.7887 5396,-412.8597 5396,-404.3198\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5399.5001,-404.1841 5396,-394.1841 5392.5001,-404.1841 5399.5001,-404.1841\"/>\n</g>\n<!-- 96 -->\n<g id=\"node97\" class=\"node\">\n<title>96</title>\n<path fill=\"#f1bc95\" stroke=\"#000000\" d=\"M7203,-394C7203,-394 7099,-394 7099,-394 7093,-394 7087,-388 7087,-382 7087,-382 7087,-353 7087,-353 7087,-347 7093,-341 7099,-341 7099,-341 7203,-341 7203,-341 7209,-341 7215,-347 7215,-353 7215,-353 7215,-382 7215,-382 7215,-388 7209,-394 7203,-394\"/>\n<text text-anchor=\"middle\" x=\"7151\" y=\"-378.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">year &lt;= 0.5</text>\n<text text-anchor=\"middle\" x=\"7151\" y=\"-363.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 39.4%</text>\n<text text-anchor=\"middle\" x=\"7151\" y=\"-348.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 126.7</text>\n</g>\n<!-- 64&#45;&gt;96 -->\n<g id=\"edge96\" class=\"edge\">\n<title>64&#45;&gt;96</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5465.6096,-452.9699C5745.5846,-438.7718 6788.2112,-385.8978 7076.639,-371.271\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7077.1738,-374.7485 7086.9837,-370.7464 7076.8192,-367.7575 7077.1738,-374.7485\"/>\n</g>\n<!-- 66 -->\n<g id=\"node67\" class=\"node\">\n<title>66</title>\n<path fill=\"#f9e4d5\" stroke=\"#000000\" d=\"M5286,-305C5286,-305 5182,-305 5182,-305 5176,-305 5170,-299 5170,-293 5170,-293 5170,-264 5170,-264 5170,-258 5176,-252 5182,-252 5182,-252 5286,-252 5286,-252 5292,-252 5298,-258 5298,-264 5298,-264 5298,-293 5298,-293 5298,-299 5292,-305 5286,-305\"/>\n<text text-anchor=\"middle\" x=\"5234\" y=\"-289.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">season &lt;= 2.5</text>\n<text text-anchor=\"middle\" x=\"5234\" y=\"-274.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 16.4%</text>\n<text text-anchor=\"middle\" x=\"5234\" y=\"-259.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;63.6</text>\n</g>\n<!-- 65&#45;&gt;66 -->\n<g id=\"edge66\" class=\"edge\">\n<title>65&#45;&gt;66</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5347.3947,-340.7971C5329.694,-331.0727 5309.5224,-319.9907 5291.1485,-309.8964\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5292.7414,-306.7781 5282.2917,-305.0306 5289.3709,-312.9133 5292.7414,-306.7781\"/>\n</g>\n<!-- 81 -->\n<g id=\"node82\" class=\"node\">\n<title>81</title>\n<path fill=\"#f5ceb2\" stroke=\"#000000\" d=\"M5861.5,-305C5861.5,-305 5734.5,-305 5734.5,-305 5728.5,-305 5722.5,-299 5722.5,-293 5722.5,-293 5722.5,-264 5722.5,-264 5722.5,-258 5728.5,-252 5734.5,-252 5734.5,-252 5861.5,-252 5861.5,-252 5867.5,-252 5873.5,-258 5873.5,-264 5873.5,-264 5873.5,-293 5873.5,-293 5873.5,-299 5867.5,-305 5861.5,-305\"/>\n<text text-anchor=\"middle\" x=\"5798\" y=\"-289.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">hour_of_day &lt;= 19.5</text>\n<text text-anchor=\"middle\" x=\"5798\" y=\"-274.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 15.5%</text>\n<text text-anchor=\"middle\" x=\"5798\" y=\"-259.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 40.3</text>\n</g>\n<!-- 65&#45;&gt;81 -->\n<g id=\"edge81\" class=\"edge\">\n<title>65&#45;&gt;81</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5460.1426,-353.2993C5528.4536,-338.1757 5636.9274,-314.1603 5712.4709,-297.4356\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5713.4333,-300.8073 5722.4403,-295.2284 5711.9202,-293.9728 5713.4333,-300.8073\"/>\n</g>\n<!-- 67 -->\n<g id=\"node68\" class=\"node\">\n<title>67</title>\n<path fill=\"#fbeade\" stroke=\"#000000\" d=\"M4928.5,-216C4928.5,-216 4801.5,-216 4801.5,-216 4795.5,-216 4789.5,-210 4789.5,-204 4789.5,-204 4789.5,-175 4789.5,-175 4789.5,-169 4795.5,-163 4801.5,-163 4801.5,-163 4928.5,-163 4928.5,-163 4934.5,-163 4940.5,-169 4940.5,-175 4940.5,-175 4940.5,-204 4940.5,-204 4940.5,-210 4934.5,-216 4928.5,-216\"/>\n<text text-anchor=\"middle\" x=\"4865\" y=\"-200.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">hour_of_day &lt;= 19.5</text>\n<text text-anchor=\"middle\" x=\"4865\" y=\"-185.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 10.9%</text>\n<text text-anchor=\"middle\" x=\"4865\" y=\"-170.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;90.2</text>\n</g>\n<!-- 66&#45;&gt;67 -->\n<g id=\"edge67\" class=\"edge\">\n<title>66&#45;&gt;67</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5169.7251,-262.9974C5109.0363,-248.3597 5017.6079,-226.3079 4950.7306,-210.1776\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"4951.1747,-206.6844 4940.6328,-207.7421 4949.5334,-213.4893 4951.1747,-206.6844\"/>\n</g>\n<!-- 74 -->\n<g id=\"node75\" class=\"node\">\n<title>74</title>\n<path fill=\"#f7d9c3\" stroke=\"#000000\" d=\"M5297.5,-216C5297.5,-216 5170.5,-216 5170.5,-216 5164.5,-216 5158.5,-210 5158.5,-204 5158.5,-204 5158.5,-175 5158.5,-175 5158.5,-169 5164.5,-163 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class=\"node\">\n<title>68</title>\n<path fill=\"#fae7d9\" stroke=\"#000000\" d=\"M4706,-127C4706,-127 4522,-127 4522,-127 4516,-127 4510,-121 4510,-115 4510,-115 4510,-86 4510,-86 4510,-80 4516,-74 4522,-74 4522,-74 4706,-74 4706,-74 4712,-74 4718,-80 4718,-86 4718,-86 4718,-115 4718,-115 4718,-121 4712,-127 4706,-127\"/>\n<text text-anchor=\"middle\" x=\"4614\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">feels_like_temperature &lt;= 0.3</text>\n<text text-anchor=\"middle\" x=\"4614\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 8.1%</text>\n<text text-anchor=\"middle\" x=\"4614\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;74.6</text>\n</g>\n<!-- 67&#45;&gt;68 -->\n<g id=\"edge68\" class=\"edge\">\n<title>67&#45;&gt;68</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M4790.0317,-162.9176C4761.2247,-152.7032 4728.1535,-140.9767 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71&#45;&gt;72 -->\n<g id=\"edge72\" class=\"edge\">\n<title>71&#45;&gt;72</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M4827.9996,-73.8139C4814.7994,-64.2934 4799.9808,-53.6056 4786.9579,-44.213\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"4788.8524,-41.2641 4778.6944,-38.2531 4784.7576,-46.9415 4788.8524,-41.2641\"/>\n</g>\n<!-- 73 -->\n<g id=\"node74\" class=\"node\">\n<title>73</title>\n<path fill=\"#fae9dd\" stroke=\"#000000\" d=\"M4938,-38C4938,-38 4842,-38 4842,-38 4836,-38 4830,-32 4830,-26 4830,-26 4830,-12 4830,-12 4830,-6 4836,0 4842,0 4842,0 4938,0 4938,0 4944,0 4950,-6 4950,-12 4950,-12 4950,-26 4950,-26 4950,-32 4944,-38 4938,-38\"/>\n<text text-anchor=\"middle\" x=\"4890\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.4%</text>\n<text text-anchor=\"middle\" x=\"4890\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;86.5</text>\n</g>\n<!-- 71&#45;&gt;73 -->\n<g id=\"edge73\" class=\"edge\">\n<title>71&#45;&gt;73</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M4873.1859,-73.8139C4875.7169,-65.5628 4878.5169,-56.4349 4881.0941,-48.0333\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"4884.5076,-48.8398 4884.0942,-38.2531 4877.8154,-46.787 4884.5076,-48.8398\"/>\n</g>\n<!-- 75 -->\n<g id=\"node76\" class=\"node\">\n<title>75</title>\n<path fill=\"#f6d4bb\" stroke=\"#000000\" d=\"M5219.5,-127C5219.5,-127 5068.5,-127 5068.5,-127 5062.5,-127 5056.5,-121 5056.5,-115 5056.5,-115 5056.5,-86 5056.5,-86 5056.5,-80 5062.5,-74 5068.5,-74 5068.5,-74 5219.5,-74 5219.5,-74 5225.5,-74 5231.5,-80 5231.5,-86 5231.5,-86 5231.5,-115 5231.5,-115 5231.5,-121 5225.5,-127 5219.5,-127\"/>\n<text text-anchor=\"middle\" x=\"5144\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">weather_situation &lt;= 2.5</text>\n<text text-anchor=\"middle\" x=\"5144\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 4.3%</text>\n<text text-anchor=\"middle\" x=\"5144\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 14.4</text>\n</g>\n<!-- 74&#45;&gt;75 -->\n<g id=\"edge75\" class=\"edge\">\n<title>74&#45;&gt;75</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5206.997,-162.7971C5197.9198,-153.8207 5187.6728,-143.6876 5178.1214,-134.2423\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5180.5554,-131.7269 5170.9839,-127.1841 5175.6334,-136.7042 5180.5554,-131.7269\"/>\n</g>\n<!-- 78 -->\n<g id=\"node79\" class=\"node\">\n<title>78</title>\n<path fill=\"#fbede2\" stroke=\"#000000\" d=\"M5388.5,-127C5388.5,-127 5261.5,-127 5261.5,-127 5255.5,-127 5249.5,-121 5249.5,-115 5249.5,-115 5249.5,-86 5249.5,-86 5249.5,-80 5255.5,-74 5261.5,-74 5261.5,-74 5388.5,-74 5388.5,-74 5394.5,-74 5400.5,-80 5400.5,-86 5400.5,-86 5400.5,-115 5400.5,-115 5400.5,-121 5394.5,-127 5388.5,-127\"/>\n<text text-anchor=\"middle\" x=\"5325\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">hour_of_day &lt;= 21.5</text>\n<text text-anchor=\"middle\" x=\"5325\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1.2%</text>\n<text text-anchor=\"middle\" x=\"5325\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;103.1</text>\n</g>\n<!-- 74&#45;&gt;78 -->\n<g id=\"edge78\" class=\"edge\">\n<title>74&#45;&gt;78</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5261.303,-162.7971C5270.4811,-153.8207 5280.8419,-143.6876 5290.4994,-134.2423\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5293.0143,-136.6784 5297.7163,-127.1841 5288.1198,-131.674 5293.0143,-136.6784\"/>\n</g>\n<!-- 76 -->\n<g id=\"node77\" class=\"node\">\n<title>76</title>\n<path fill=\"#f5d0b6\" stroke=\"#000000\" d=\"M5076,-38C5076,-38 4980,-38 4980,-38 4974,-38 4968,-32 4968,-26 4968,-26 4968,-12 4968,-12 4968,-6 4974,0 4980,0 4980,0 5076,0 5076,0 5082,0 5088,-6 5088,-12 5088,-12 5088,-26 5088,-26 5088,-32 5082,-38 5076,-38\"/>\n<text text-anchor=\"middle\" x=\"5028\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 3.7%</text>\n<text text-anchor=\"middle\" x=\"5028\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 29.4</text>\n</g>\n<!-- 75&#45;&gt;76 -->\n<g id=\"edge76\" class=\"edge\">\n<title>75&#45;&gt;76</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5106.0173,-73.8139C5092.4667,-64.2934 5077.2546,-53.6056 5063.886,-44.213\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5065.5976,-41.1381 5055.4031,-38.2531 5061.5734,-46.8658 5065.5976,-41.1381\"/>\n</g>\n<!-- 77 -->\n<g id=\"node78\" class=\"node\">\n<title>77</title>\n<path fill=\"#fae9dc\" stroke=\"#000000\" d=\"M5214,-38C5214,-38 5118,-38 5118,-38 5112,-38 5106,-32 5106,-26 5106,-26 5106,-12 5106,-12 5106,-6 5112,0 5118,0 5118,0 5214,0 5214,0 5220,0 5226,-6 5226,-12 5226,-12 5226,-26 5226,-26 5226,-32 5220,-38 5214,-38\"/>\n<text text-anchor=\"middle\" x=\"5166\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.6%</text>\n<text text-anchor=\"middle\" x=\"5166\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;85.0</text>\n</g>\n<!-- 75&#45;&gt;77 -->\n<g id=\"edge77\" class=\"edge\">\n<title>75&#45;&gt;77</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5151.2036,-73.8139C5153.4309,-65.5628 5155.8949,-56.4349 5158.1628,-48.0333\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5161.5757,-48.8197 5160.8029,-38.2531 5154.8176,-46.9953 5161.5757,-48.8197\"/>\n</g>\n<!-- 79 -->\n<g id=\"node80\" class=\"node\">\n<title>79</title>\n<path fill=\"#fae7da\" stroke=\"#000000\" d=\"M5352,-38C5352,-38 5256,-38 5256,-38 5250,-38 5244,-32 5244,-26 5244,-26 5244,-12 5244,-12 5244,-6 5250,0 5256,0 5256,0 5352,0 5352,0 5358,0 5364,-6 5364,-12 5364,-12 5364,-26 5364,-26 5364,-32 5358,-38 5352,-38\"/>\n<text text-anchor=\"middle\" x=\"5304\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.4%</text>\n<text text-anchor=\"middle\" x=\"5304\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;78.6</text>\n</g>\n<!-- 78&#45;&gt;79 -->\n<g id=\"edge79\" class=\"edge\">\n<title>78&#45;&gt;79</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5318.1238,-73.8139C5315.9978,-65.5628 5313.6458,-56.4349 5311.481,-48.0333\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5314.8455,-47.0634 5308.9609,-38.2531 5308.0669,-48.8101 5314.8455,-47.0634\"/>\n</g>\n<!-- 80 -->\n<g id=\"node81\" class=\"node\">\n<title>80</title>\n<path fill=\"#fcefe6\" stroke=\"#000000\" d=\"M5490,-38C5490,-38 5394,-38 5394,-38 5388,-38 5382,-32 5382,-26 5382,-26 5382,-12 5382,-12 5382,-6 5388,0 5394,0 5394,0 5490,0 5490,0 5496,0 5502,-6 5502,-12 5502,-12 5502,-26 5502,-26 5502,-32 5496,-38 5490,-38\"/>\n<text text-anchor=\"middle\" x=\"5442\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.8%</text>\n<text text-anchor=\"middle\" x=\"5442\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;114.7</text>\n</g>\n<!-- 78&#45;&gt;80 -->\n<g id=\"edge80\" class=\"edge\">\n<title>78&#45;&gt;80</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5363.3102,-73.8139C5376.9776,-64.2934 5392.3208,-53.6056 5405.8046,-44.213\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5408.1557,-46.8408 5414.3606,-38.2531 5404.1546,-41.097 5408.1557,-46.8408\"/>\n</g>\n<!-- 82 -->\n<g id=\"node83\" class=\"node\">\n<title>82</title>\n<path fill=\"#f3c7a7\" stroke=\"#000000\" d=\"M5850,-216C5850,-216 5746,-216 5746,-216 5740,-216 5734,-210 5734,-204 5734,-204 5734,-175 5734,-175 5734,-169 5740,-163 5746,-163 5746,-163 5850,-163 5850,-163 5856,-163 5862,-169 5862,-175 5862,-175 5862,-204 5862,-204 5862,-210 5856,-216 5850,-216\"/>\n<text text-anchor=\"middle\" x=\"5798\" y=\"-200.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">season &lt;= 1.5</text>\n<text text-anchor=\"middle\" x=\"5798\" y=\"-185.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 11.7%</text>\n<text text-anchor=\"middle\" x=\"5798\" y=\"-170.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 74.0</text>\n</g>\n<!-- 81&#45;&gt;82 -->\n<g id=\"edge82\" class=\"edge\">\n<title>81&#45;&gt;82</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5798,-251.7971C5798,-243.7887 5798,-234.8597 5798,-226.3198\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5801.5001,-226.1841 5798,-216.1841 5794.5001,-226.1841 5801.5001,-226.1841\"/>\n</g>\n<!-- 89 -->\n<g id=\"node90\" class=\"node\">\n<title>89</title>\n<path fill=\"#f9e4d5\" stroke=\"#000000\" d=\"M6220.5,-216C6220.5,-216 6093.5,-216 6093.5,-216 6087.5,-216 6081.5,-210 6081.5,-204 6081.5,-204 6081.5,-175 6081.5,-175 6081.5,-169 6087.5,-163 6093.5,-163 6093.5,-163 6220.5,-163 6220.5,-163 6226.5,-163 6232.5,-169 6232.5,-175 6232.5,-175 6232.5,-204 6232.5,-204 6232.5,-210 6226.5,-216 6220.5,-216\"/>\n<text text-anchor=\"middle\" x=\"6157\" y=\"-200.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">hour_of_day &lt;= 21.5</text>\n<text text-anchor=\"middle\" x=\"6157\" y=\"-185.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 3.8%</text>\n<text text-anchor=\"middle\" x=\"6157\" y=\"-170.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;63.7</text>\n</g>\n<!-- 81&#45;&gt;89 -->\n<g id=\"edge89\" class=\"edge\">\n<title>81&#45;&gt;89</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5873.696,-259.7341C5931.5717,-245.3861 6011.3834,-225.5999 6071.5491,-210.6842\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"6072.5436,-214.0437 6081.4076,-208.2402 6070.8592,-207.2494 6072.5436,-214.0437\"/>\n</g>\n<!-- 83 -->\n<g id=\"node84\" class=\"node\">\n<title>83</title>\n<path fill=\"#f6d4bc\" stroke=\"#000000\" d=\"M5785,-127C5785,-127 5601,-127 5601,-127 5595,-127 5589,-121 5589,-115 5589,-115 5589,-86 5589,-86 5589,-80 5595,-74 5601,-74 5601,-74 5785,-74 5785,-74 5791,-74 5797,-80 5797,-86 5797,-86 5797,-115 5797,-115 5797,-121 5791,-127 5785,-127\"/>\n<text text-anchor=\"middle\" x=\"5693\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">feels_like_temperature &lt;= 0.3</text>\n<text text-anchor=\"middle\" x=\"5693\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 5.8%</text>\n<text text-anchor=\"middle\" x=\"5693\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 11.3</text>\n</g>\n<!-- 82&#45;&gt;83 -->\n<g id=\"edge83\" class=\"edge\">\n<title>82&#45;&gt;83</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5766.4965,-162.7971C5755.6988,-153.6447 5743.4823,-143.2898 5732.1538,-133.6875\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5734.3727,-130.9801 5724.4812,-127.1841 5729.8465,-136.32 5734.3727,-130.9801\"/>\n</g>\n<!-- 86 -->\n<g id=\"node87\" class=\"node\">\n<title>86</title>\n<path fill=\"#f1ba92\" stroke=\"#000000\" d=\"M5978.5,-127C5978.5,-127 5827.5,-127 5827.5,-127 5821.5,-127 5815.5,-121 5815.5,-115 5815.5,-115 5815.5,-86 5815.5,-86 5815.5,-80 5821.5,-74 5827.5,-74 5827.5,-74 5978.5,-74 5978.5,-74 5984.5,-74 5990.5,-80 5990.5,-86 5990.5,-86 5990.5,-115 5990.5,-115 5990.5,-121 5984.5,-127 5978.5,-127\"/>\n<text text-anchor=\"middle\" x=\"5903\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">weather_situation &lt;= 2.5</text>\n<text text-anchor=\"middle\" x=\"5903\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 5.9%</text>\n<text text-anchor=\"middle\" x=\"5903\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 135.4</text>\n</g>\n<!-- 82&#45;&gt;86 -->\n<g id=\"edge86\" class=\"edge\">\n<title>82&#45;&gt;86</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5829.5035,-162.7971C5840.3012,-153.6447 5852.5177,-143.2898 5863.8462,-133.6875\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5866.1535,-136.32 5871.5188,-127.1841 5861.6273,-130.9801 5866.1535,-136.32\"/>\n</g>\n<!-- 84 -->\n<g id=\"node85\" class=\"node\">\n<title>84</title>\n<path fill=\"#f8ddc9\" stroke=\"#000000\" d=\"M5628,-38C5628,-38 5532,-38 5532,-38 5526,-38 5520,-32 5520,-26 5520,-26 5520,-12 5520,-12 5520,-6 5526,0 5532,0 5532,0 5628,0 5628,0 5634,0 5640,-6 5640,-12 5640,-12 5640,-26 5640,-26 5640,-32 5634,-38 5628,-38\"/>\n<text text-anchor=\"middle\" x=\"5580\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 3.1%</text>\n<text text-anchor=\"middle\" x=\"5580\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;28.9</text>\n</g>\n<!-- 83&#45;&gt;84 -->\n<g id=\"edge84\" class=\"edge\">\n<title>83&#45;&gt;84</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5655.9996,-73.8139C5642.7994,-64.2934 5627.9808,-53.6056 5614.9579,-44.213\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5616.8524,-41.2641 5606.6944,-38.2531 5612.7576,-46.9415 5616.8524,-41.2641\"/>\n</g>\n<!-- 85 -->\n<g id=\"node86\" class=\"node\">\n<title>85</title>\n<path fill=\"#f4caac\" stroke=\"#000000\" d=\"M5766,-38C5766,-38 5670,-38 5670,-38 5664,-38 5658,-32 5658,-26 5658,-26 5658,-12 5658,-12 5658,-6 5664,0 5670,0 5670,0 5766,0 5766,0 5772,0 5778,-6 5778,-12 5778,-12 5778,-26 5778,-26 5778,-32 5772,-38 5766,-38\"/>\n<text text-anchor=\"middle\" x=\"5718\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 2.7%</text>\n<text text-anchor=\"middle\" x=\"5718\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 58.8</text>\n</g>\n<!-- 83&#45;&gt;85 -->\n<g id=\"edge85\" class=\"edge\">\n<title>83&#45;&gt;85</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5701.1859,-73.8139C5703.7169,-65.5628 5706.5169,-56.4349 5709.0941,-48.0333\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5712.5076,-48.8398 5712.0942,-38.2531 5705.8154,-46.787 5712.5076,-48.8398\"/>\n</g>\n<!-- 87 -->\n<g id=\"node88\" class=\"node\">\n<title>87</title>\n<path fill=\"#f0b78e\" stroke=\"#000000\" d=\"M5904,-38C5904,-38 5808,-38 5808,-38 5802,-38 5796,-32 5796,-26 5796,-26 5796,-12 5796,-12 5796,-6 5802,0 5808,0 5808,0 5904,0 5904,0 5910,0 5916,-6 5916,-12 5916,-12 5916,-26 5916,-26 5916,-32 5910,-38 5904,-38\"/>\n<text text-anchor=\"middle\" x=\"5856\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 5.4%</text>\n<text text-anchor=\"middle\" x=\"5856\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 148.1</text>\n</g>\n<!-- 86&#45;&gt;87 -->\n<g id=\"edge87\" class=\"edge\">\n<title>86&#45;&gt;87</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5887.6104,-73.8139C5882.643,-65.2001 5877.1245,-55.6308 5872.1067,-46.9297\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5875.1307,-45.1673 5867.103,-38.2531 5869.0668,-48.6643 5875.1307,-45.1673\"/>\n</g>\n<!-- 88 -->\n<g id=\"node89\" class=\"node\">\n<title>88</title>\n<path fill=\"#f7d7c0\" stroke=\"#000000\" d=\"M6042,-38C6042,-38 5946,-38 5946,-38 5940,-38 5934,-32 5934,-26 5934,-26 5934,-12 5934,-12 5934,-6 5940,0 5946,0 5946,0 6042,0 6042,0 6048,0 6054,-6 6054,-12 6054,-12 6054,-26 6054,-26 6054,-32 6048,-38 6042,-38\"/>\n<text text-anchor=\"middle\" x=\"5994\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.5%</text>\n<text text-anchor=\"middle\" x=\"5994\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;1.5</text>\n</g>\n<!-- 86&#45;&gt;88 -->\n<g id=\"edge88\" class=\"edge\">\n<title>86&#45;&gt;88</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M5932.7968,-73.8139C5943.1233,-64.5654 5954.6798,-54.2154 5964.9456,-45.0212\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"5967.3885,-47.5319 5972.5027,-38.2531 5962.7184,-42.3174 5967.3885,-47.5319\"/>\n</g>\n<!-- 90 -->\n<g id=\"node91\" class=\"node\">\n<title>90</title>\n<path fill=\"#f8dcc8\" stroke=\"#000000\" d=\"M6249,-127C6249,-127 6065,-127 6065,-127 6059,-127 6053,-121 6053,-115 6053,-115 6053,-86 6053,-86 6053,-80 6059,-74 6065,-74 6065,-74 6249,-74 6249,-74 6255,-74 6261,-80 6261,-86 6261,-86 6261,-115 6261,-115 6261,-121 6255,-127 6249,-127\"/>\n<text text-anchor=\"middle\" x=\"6157\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">feels_like_temperature &lt;= 0.3</text>\n<text text-anchor=\"middle\" x=\"6157\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1.8%</text>\n<text text-anchor=\"middle\" x=\"6157\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;25.2</text>\n</g>\n<!-- 89&#45;&gt;90 -->\n<g id=\"edge90\" class=\"edge\">\n<title>89&#45;&gt;90</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M6157,-162.7971C6157,-154.7887 6157,-145.8597 6157,-137.3198\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"6160.5001,-137.1841 6157,-127.1841 6153.5001,-137.1841 6160.5001,-137.1841\"/>\n</g>\n<!-- 93 -->\n<g id=\"node94\" class=\"node\">\n<title>93</title>\n<path fill=\"#fbece1\" stroke=\"#000000\" d=\"M6456,-127C6456,-127 6360,-127 6360,-127 6354,-127 6348,-121 6348,-115 6348,-115 6348,-86 6348,-86 6348,-80 6354,-74 6360,-74 6360,-74 6456,-74 6456,-74 6462,-74 6468,-80 6468,-86 6468,-86 6468,-115 6468,-115 6468,-121 6462,-127 6456,-127\"/>\n<text text-anchor=\"middle\" x=\"6408\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">season &lt;= 1.5</text>\n<text text-anchor=\"middle\" x=\"6408\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1.9%</text>\n<text text-anchor=\"middle\" x=\"6408\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;100.2</text>\n</g>\n<!-- 89&#45;&gt;93 -->\n<g id=\"edge93\" class=\"edge\">\n<title>89&#45;&gt;93</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M6231.9683,-162.9176C6265.6264,-150.9831 6305.1059,-136.9844 6338.1379,-125.2718\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"6339.4643,-128.5151 6347.7196,-121.8743 6337.1249,-121.9176 6339.4643,-128.5151\"/>\n</g>\n<!-- 91 -->\n<g id=\"node92\" class=\"node\">\n<title>91</title>\n<path fill=\"#fae8db\" stroke=\"#000000\" d=\"M6180,-38C6180,-38 6084,-38 6084,-38 6078,-38 6072,-32 6072,-26 6072,-26 6072,-12 6072,-12 6072,-6 6078,0 6084,0 6084,0 6180,0 6180,0 6186,0 6192,-6 6192,-12 6192,-12 6192,-26 6192,-26 6192,-32 6186,-38 6180,-38\"/>\n<text text-anchor=\"middle\" x=\"6132\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.5%</text>\n<text text-anchor=\"middle\" x=\"6132\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;83.2</text>\n</g>\n<!-- 90&#45;&gt;91 -->\n<g id=\"edge91\" class=\"edge\">\n<title>90&#45;&gt;91</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M6148.8141,-73.8139C6146.2831,-65.5628 6143.4831,-56.4349 6140.9059,-48.0333\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"6144.1846,-46.787 6137.9058,-38.2531 6137.4924,-48.8398 6144.1846,-46.787\"/>\n</g>\n<!-- 92 -->\n<g id=\"node93\" class=\"node\">\n<title>92</title>\n<path fill=\"#f7d8c2\" stroke=\"#000000\" d=\"M6318,-38C6318,-38 6222,-38 6222,-38 6216,-38 6210,-32 6210,-26 6210,-26 6210,-12 6210,-12 6210,-6 6216,0 6222,0 6222,0 6318,0 6318,0 6324,0 6330,-6 6330,-12 6330,-12 6330,-26 6330,-26 6330,-32 6324,-38 6318,-38\"/>\n<text text-anchor=\"middle\" x=\"6270\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1.4%</text>\n<text text-anchor=\"middle\" x=\"6270\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;5.9</text>\n</g>\n<!-- 90&#45;&gt;92 -->\n<g id=\"edge92\" class=\"edge\">\n<title>90&#45;&gt;92</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M6194.0004,-73.8139C6207.2006,-64.2934 6222.0192,-53.6056 6235.0421,-44.213\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"6237.2424,-46.9415 6243.3056,-38.2531 6233.1476,-41.2641 6237.2424,-46.9415\"/>\n</g>\n<!-- 94 -->\n<g id=\"node95\" class=\"node\">\n<title>94</title>\n<path fill=\"#fcf1e9\" stroke=\"#000000\" d=\"M6456,-38C6456,-38 6360,-38 6360,-38 6354,-38 6348,-32 6348,-26 6348,-26 6348,-12 6348,-12 6348,-6 6354,0 6360,0 6360,0 6456,0 6456,0 6462,0 6468,-6 6468,-12 6468,-12 6468,-26 6468,-26 6468,-32 6462,-38 6456,-38\"/>\n<text text-anchor=\"middle\" x=\"6408\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.9%</text>\n<text text-anchor=\"middle\" x=\"6408\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;123.0</text>\n</g>\n<!-- 93&#45;&gt;94 -->\n<g id=\"edge94\" class=\"edge\">\n<title>93&#45;&gt;94</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M6408,-73.8139C6408,-65.6535 6408,-56.6354 6408,-48.3105\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"6411.5001,-48.253 6408,-38.2531 6404.5001,-48.2531 6411.5001,-48.253\"/>\n</g>\n<!-- 95 -->\n<g id=\"node96\" class=\"node\">\n<title>95</title>\n<path fill=\"#fae8db\" stroke=\"#000000\" d=\"M6594,-38C6594,-38 6498,-38 6498,-38 6492,-38 6486,-32 6486,-26 6486,-26 6486,-12 6486,-12 6486,-6 6492,0 6498,0 6498,0 6594,0 6594,0 6600,0 6606,-6 6606,-12 6606,-12 6606,-26 6606,-26 6606,-32 6600,-38 6594,-38\"/>\n<text text-anchor=\"middle\" x=\"6546\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1.0%</text>\n<text text-anchor=\"middle\" x=\"6546\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;80.5</text>\n</g>\n<!-- 93&#45;&gt;95 -->\n<g id=\"edge95\" class=\"edge\">\n<title>93&#45;&gt;95</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M6453.1864,-73.8139C6469.7675,-64.0214 6488.4397,-52.9939 6504.6658,-43.4112\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"6506.569,-46.352 6513.3997,-38.2531 6503.0094,-40.3246 6506.569,-46.352\"/>\n</g>\n<!-- 97 -->\n<g id=\"node98\" class=\"node\">\n<title>97</title>\n<path fill=\"#f4cbad\" stroke=\"#000000\" d=\"M7214.5,-305C7214.5,-305 7087.5,-305 7087.5,-305 7081.5,-305 7075.5,-299 7075.5,-293 7075.5,-293 7075.5,-264 7075.5,-264 7075.5,-258 7081.5,-252 7087.5,-252 7087.5,-252 7214.5,-252 7214.5,-252 7220.5,-252 7226.5,-258 7226.5,-264 7226.5,-264 7226.5,-293 7226.5,-293 7226.5,-299 7220.5,-305 7214.5,-305\"/>\n<text text-anchor=\"middle\" x=\"7151\" y=\"-289.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">hour_of_day &lt;= 20.5</text>\n<text text-anchor=\"middle\" x=\"7151\" y=\"-274.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 19.1%</text>\n<text text-anchor=\"middle\" x=\"7151\" y=\"-259.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 55.2</text>\n</g>\n<!-- 96&#45;&gt;97 -->\n<g id=\"edge97\" class=\"edge\">\n<title>96&#45;&gt;97</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7151,-340.7971C7151,-332.7887 7151,-323.8597 7151,-315.3198\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7154.5001,-315.1841 7151,-305.1841 7147.5001,-315.1841 7154.5001,-315.1841\"/>\n</g>\n<!-- 112 -->\n<g id=\"node113\" class=\"node\">\n<title>112</title>\n<path fill=\"#eead7f\" stroke=\"#000000\" d=\"M8057.5,-305C8057.5,-305 7930.5,-305 7930.5,-305 7924.5,-305 7918.5,-299 7918.5,-293 7918.5,-293 7918.5,-264 7918.5,-264 7918.5,-258 7924.5,-252 7930.5,-252 7930.5,-252 8057.5,-252 8057.5,-252 8063.5,-252 8069.5,-258 8069.5,-264 8069.5,-264 8069.5,-293 8069.5,-293 8069.5,-299 8063.5,-305 8057.5,-305\"/>\n<text text-anchor=\"middle\" x=\"7994\" y=\"-289.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">hour_of_day &lt;= 20.5</text>\n<text text-anchor=\"middle\" x=\"7994\" y=\"-274.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 20.3%</text>\n<text text-anchor=\"middle\" x=\"7994\" y=\"-259.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 193.8</text>\n</g>\n<!-- 96&#45;&gt;112 -->\n<g id=\"edge112\" class=\"edge\">\n<title>96&#45;&gt;112</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7215.0539,-360.7375C7365.0107,-344.9057 7738.9546,-305.4265 7908.2817,-287.5497\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7908.822,-291.0122 7918.3992,-286.4816 7908.087,-284.0509 7908.822,-291.0122\"/>\n</g>\n<!-- 98 -->\n<g id=\"node99\" class=\"node\">\n<title>98</title>\n<path fill=\"#f3c6a6\" stroke=\"#000000\" d=\"M7093.5,-216C7093.5,-216 6966.5,-216 6966.5,-216 6960.5,-216 6954.5,-210 6954.5,-204 6954.5,-204 6954.5,-175 6954.5,-175 6954.5,-169 6960.5,-163 6966.5,-163 6966.5,-163 7093.5,-163 7093.5,-163 7099.5,-163 7105.5,-169 7105.5,-175 7105.5,-175 7105.5,-204 7105.5,-204 7105.5,-210 7099.5,-216 7093.5,-216\"/>\n<text text-anchor=\"middle\" x=\"7030\" y=\"-200.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">hour_of_day &lt;= 15.5</text>\n<text text-anchor=\"middle\" x=\"7030\" y=\"-185.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 15.9%</text>\n<text text-anchor=\"middle\" x=\"7030\" y=\"-170.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 75.7</text>\n</g>\n<!-- 97&#45;&gt;98 -->\n<g id=\"edge98\" class=\"edge\">\n<title>97&#45;&gt;98</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7114.696,-251.7971C7102.0136,-242.4687 7087.6328,-231.8911 7074.3681,-222.1344\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7076.4078,-219.2898 7066.2784,-216.1841 7072.2601,-224.9288 7076.4078,-219.2898\"/>\n</g>\n<!-- 105 -->\n<g id=\"node106\" class=\"node\">\n<title>105</title>\n<path fill=\"#f9e1d0\" stroke=\"#000000\" d=\"M7368.5,-216C7368.5,-216 7241.5,-216 7241.5,-216 7235.5,-216 7229.5,-210 7229.5,-204 7229.5,-204 7229.5,-175 7229.5,-175 7229.5,-169 7235.5,-163 7241.5,-163 7241.5,-163 7368.5,-163 7368.5,-163 7374.5,-163 7380.5,-169 7380.5,-175 7380.5,-175 7380.5,-204 7380.5,-204 7380.5,-210 7374.5,-216 7368.5,-216\"/>\n<text text-anchor=\"middle\" x=\"7305\" y=\"-200.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">hour_of_day &lt;= 22.5</text>\n<text text-anchor=\"middle\" x=\"7305\" y=\"-185.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 3.1%</text>\n<text text-anchor=\"middle\" x=\"7305\" y=\"-170.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;50.2</text>\n</g>\n<!-- 97&#45;&gt;105 -->\n<g id=\"edge105\" class=\"edge\">\n<title>97&#45;&gt;105</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7197.2051,-251.7971C7213.8786,-242.1611 7232.8586,-231.1921 7250.1969,-221.1719\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7252.1863,-224.0647 7259.0931,-216.0306 7248.6836,-218.004 7252.1863,-224.0647\"/>\n</g>\n<!-- 99 -->\n<g id=\"node100\" class=\"node\">\n<title>99</title>\n<path fill=\"#f5d0b5\" stroke=\"#000000\" d=\"M6887,-127C6887,-127 6757,-127 6757,-127 6751,-127 6745,-121 6745,-115 6745,-115 6745,-86 6745,-86 6745,-80 6751,-74 6757,-74 6757,-74 6887,-74 6887,-74 6893,-74 6899,-80 6899,-86 6899,-86 6899,-115 6899,-115 6899,-121 6893,-127 6887,-127\"/>\n<text text-anchor=\"middle\" x=\"6822\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">is_workingday &lt;= 0.5</text>\n<text text-anchor=\"middle\" x=\"6822\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 10.1%</text>\n<text text-anchor=\"middle\" x=\"6822\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 30.2</text>\n</g>\n<!-- 98&#45;&gt;99 -->\n<g id=\"edge99\" class=\"edge\">\n<title>98&#45;&gt;99</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M6967.8749,-162.9176C6944.5196,-152.9243 6917.782,-141.4837 6893.6311,-131.1498\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"6894.7348,-127.8152 6884.1642,-127.0991 6891.981,-134.2508 6894.7348,-127.8152\"/>\n</g>\n<!-- 102 -->\n<g id=\"node103\" class=\"node\">\n<title>102</title>\n<path fill=\"#f0b68c\" stroke=\"#000000\" d=\"M7093.5,-127C7093.5,-127 6966.5,-127 6966.5,-127 6960.5,-127 6954.5,-121 6954.5,-115 6954.5,-115 6954.5,-86 6954.5,-86 6954.5,-80 6960.5,-74 6966.5,-74 6966.5,-74 7093.5,-74 7093.5,-74 7099.5,-74 7105.5,-80 7105.5,-86 7105.5,-86 7105.5,-115 7105.5,-115 7105.5,-121 7099.5,-127 7093.5,-127\"/>\n<text text-anchor=\"middle\" x=\"7030\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">hour_of_day &lt;= 19.5</text>\n<text text-anchor=\"middle\" x=\"7030\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 5.8%</text>\n<text text-anchor=\"middle\" x=\"7030\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 154.2</text>\n</g>\n<!-- 98&#45;&gt;102 -->\n<g id=\"edge102\" class=\"edge\">\n<title>98&#45;&gt;102</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7030,-162.7971C7030,-154.7887 7030,-145.8597 7030,-137.3198\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7033.5001,-137.1841 7030,-127.1841 7026.5001,-137.1841 7033.5001,-137.1841\"/>\n</g>\n<!-- 100 -->\n<g id=\"node101\" class=\"node\">\n<title>100</title>\n<path fill=\"#f3c4a2\" stroke=\"#000000\" d=\"M6732,-38C6732,-38 6636,-38 6636,-38 6630,-38 6624,-32 6624,-26 6624,-26 6624,-12 6624,-12 6624,-6 6630,0 6636,0 6636,0 6732,0 6732,0 6738,0 6744,-6 6744,-12 6744,-12 6744,-26 6744,-26 6744,-32 6738,-38 6732,-38\"/>\n<text text-anchor=\"middle\" x=\"6684\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 2.8%</text>\n<text text-anchor=\"middle\" x=\"6684\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 87.6</text>\n</g>\n<!-- 99&#45;&gt;100 -->\n<g id=\"edge100\" class=\"edge\">\n<title>99&#45;&gt;100</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M6776.8136,-73.8139C6760.2325,-64.0214 6741.5603,-52.9939 6725.3342,-43.4112\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"6726.9906,-40.3246 6716.6003,-38.2531 6723.431,-46.352 6726.9906,-40.3246\"/>\n</g>\n<!-- 101 -->\n<g id=\"node102\" class=\"node\">\n<title>101</title>\n<path fill=\"#f6d5bd\" stroke=\"#000000\" d=\"M6870,-38C6870,-38 6774,-38 6774,-38 6768,-38 6762,-32 6762,-26 6762,-26 6762,-12 6762,-12 6762,-6 6768,0 6774,0 6774,0 6870,0 6870,0 6876,0 6882,-6 6882,-12 6882,-12 6882,-26 6882,-26 6882,-32 6876,-38 6870,-38\"/>\n<text text-anchor=\"middle\" x=\"6822\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 7.3%</text>\n<text text-anchor=\"middle\" x=\"6822\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 7.9</text>\n</g>\n<!-- 99&#45;&gt;101 -->\n<g id=\"edge101\" class=\"edge\">\n<title>99&#45;&gt;101</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M6822,-73.8139C6822,-65.6535 6822,-56.6354 6822,-48.3105\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"6825.5001,-48.253 6822,-38.2531 6818.5001,-48.2531 6825.5001,-48.253\"/>\n</g>\n<!-- 103 -->\n<g id=\"node104\" class=\"node\">\n<title>103</title>\n<path fill=\"#efb084\" stroke=\"#000000\" d=\"M7008,-38C7008,-38 6912,-38 6912,-38 6906,-38 6900,-32 6900,-26 6900,-26 6900,-12 6900,-12 6900,-6 6906,0 6912,0 6912,0 7008,0 7008,0 7014,0 7020,-6 7020,-12 7020,-12 7020,-26 7020,-26 7020,-32 7014,-38 7008,-38\"/>\n<text text-anchor=\"middle\" x=\"6960\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 4.8%</text>\n<text text-anchor=\"middle\" x=\"6960\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 178.9</text>\n</g>\n<!-- 102&#45;&gt;103 -->\n<g id=\"edge103\" class=\"edge\">\n<title>102&#45;&gt;103</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7007.0794,-73.8139C6999.4474,-64.9281 6990.9421,-55.0255 6983.283,-46.1081\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"6985.7071,-43.5586 6976.5364,-38.2531 6980.3969,-48.1195 6985.7071,-43.5586\"/>\n</g>\n<!-- 104 -->\n<g id=\"node105\" class=\"node\">\n<title>104</title>\n<path fill=\"#f5cdb0\" stroke=\"#000000\" d=\"M7146,-38C7146,-38 7050,-38 7050,-38 7044,-38 7038,-32 7038,-26 7038,-26 7038,-12 7038,-12 7038,-6 7044,0 7050,0 7050,0 7146,0 7146,0 7152,0 7158,-6 7158,-12 7158,-12 7158,-26 7158,-26 7158,-32 7152,-38 7146,-38\"/>\n<text text-anchor=\"middle\" x=\"7098\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1.1%</text>\n<text text-anchor=\"middle\" x=\"7098\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 47.2</text>\n</g>\n<!-- 102&#45;&gt;104 -->\n<g id=\"edge104\" class=\"edge\">\n<title>102&#45;&gt;104</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7052.2657,-73.8139C7059.6796,-64.9281 7067.9419,-55.0255 7075.3822,-46.1081\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7078.217,-48.1737 7081.9361,-38.2531 7072.8422,-43.6892 7078.217,-48.1737\"/>\n</g>\n<!-- 106 -->\n<g id=\"node107\" class=\"node\">\n<title>106</title>\n<path fill=\"#f8ddc9\" stroke=\"#000000\" d=\"M7353,-127C7353,-127 7257,-127 7257,-127 7251,-127 7245,-121 7245,-115 7245,-115 7245,-86 7245,-86 7245,-80 7251,-74 7257,-74 7257,-74 7353,-74 7353,-74 7359,-74 7365,-80 7365,-86 7365,-86 7365,-115 7365,-115 7365,-121 7359,-127 7353,-127\"/>\n<text text-anchor=\"middle\" x=\"7305\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">humidity &lt;= 0.8</text>\n<text text-anchor=\"middle\" x=\"7305\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 2.1%</text>\n<text text-anchor=\"middle\" x=\"7305\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;28.3</text>\n</g>\n<!-- 105&#45;&gt;106 -->\n<g id=\"edge106\" class=\"edge\">\n<title>105&#45;&gt;106</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7305,-162.7971C7305,-154.7887 7305,-145.8597 7305,-137.3198\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7308.5001,-137.1841 7305,-127.1841 7301.5001,-137.1841 7308.5001,-137.1841\"/>\n</g>\n<!-- 109 -->\n<g id=\"node110\" class=\"node\">\n<title>109</title>\n<path fill=\"#fbece1\" stroke=\"#000000\" d=\"M7560,-127C7560,-127 7464,-127 7464,-127 7458,-127 7452,-121 7452,-115 7452,-115 7452,-86 7452,-86 7452,-80 7458,-74 7464,-74 7464,-74 7560,-74 7560,-74 7566,-74 7572,-80 7572,-86 7572,-86 7572,-115 7572,-115 7572,-121 7566,-127 7560,-127\"/>\n<text text-anchor=\"middle\" x=\"7512\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">weekday &lt;= 3.5</text>\n<text text-anchor=\"middle\" x=\"7512\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1.0%</text>\n<text text-anchor=\"middle\" x=\"7512\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;98.3</text>\n</g>\n<!-- 105&#45;&gt;109 -->\n<g id=\"edge109\" class=\"edge\">\n<title>105&#45;&gt;109</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7366.8264,-162.9176C7390.7004,-152.653 7418.1258,-140.8614 7442.6651,-130.3107\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7444.1109,-133.4989 7451.9153,-126.3335 7441.3459,-127.0681 7444.1109,-133.4989\"/>\n</g>\n<!-- 107 -->\n<g id=\"node108\" class=\"node\">\n<title>107</title>\n<path fill=\"#f7dac6\" stroke=\"#000000\" d=\"M7284,-38C7284,-38 7188,-38 7188,-38 7182,-38 7176,-32 7176,-26 7176,-26 7176,-12 7176,-12 7176,-6 7182,0 7188,0 7188,0 7284,0 7284,0 7290,0 7296,-6 7296,-12 7296,-12 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7434,-26 7434,-26 7434,-32 7428,-38 7422,-38\"/>\n<text text-anchor=\"middle\" x=\"7374\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.4%</text>\n<text text-anchor=\"middle\" x=\"7374\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;75.9</text>\n</g>\n<!-- 106&#45;&gt;108 -->\n<g id=\"edge108\" class=\"edge\">\n<title>106&#45;&gt;108</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7327.5932,-73.8139C7335.1161,-64.9281 7343.4999,-55.0255 7351.0496,-46.1081\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7353.9095,-48.1467 7357.6999,-38.2531 7348.5671,-43.6236 7353.9095,-48.1467\"/>\n</g>\n<!-- 110 -->\n<g id=\"node111\" class=\"node\">\n<title>110</title>\n<path fill=\"#fcefe7\" stroke=\"#000000\" d=\"M7560,-38C7560,-38 7464,-38 7464,-38 7458,-38 7452,-32 7452,-26 7452,-26 7452,-12 7452,-12 7452,-6 7458,0 7464,0 7464,0 7560,0 7560,0 7566,0 7572,-6 7572,-12 7572,-12 7572,-26 7572,-26 7572,-32 7566,-38 7560,-38\"/>\n<text text-anchor=\"middle\" x=\"7512\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.6%</text>\n<text text-anchor=\"middle\" x=\"7512\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;116.4</text>\n</g>\n<!-- 109&#45;&gt;110 -->\n<g id=\"edge110\" class=\"edge\">\n<title>109&#45;&gt;110</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7512,-73.8139C7512,-65.6535 7512,-56.6354 7512,-48.3105\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7515.5001,-48.253 7512,-38.2531 7508.5001,-48.2531 7515.5001,-48.253\"/>\n</g>\n<!-- 111 -->\n<g id=\"node112\" class=\"node\">\n<title>111</title>\n<path fill=\"#fae6d7\" stroke=\"#000000\" d=\"M7698,-38C7698,-38 7602,-38 7602,-38 7596,-38 7590,-32 7590,-26 7590,-26 7590,-12 7590,-12 7590,-6 7596,0 7602,0 7602,0 7698,0 7698,0 7704,0 7710,-6 7710,-12 7710,-12 7710,-26 7710,-26 7710,-32 7704,-38 7698,-38\"/>\n<text text-anchor=\"middle\" x=\"7650\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.4%</text>\n<text text-anchor=\"middle\" x=\"7650\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;70.0</text>\n</g>\n<!-- 109&#45;&gt;111 -->\n<g id=\"edge111\" class=\"edge\">\n<title>109&#45;&gt;111</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7557.1864,-73.8139C7573.7675,-64.0214 7592.4397,-52.9939 7608.6658,-43.4112\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7610.569,-46.352 7617.3997,-38.2531 7607.0094,-40.3246 7610.569,-46.352\"/>\n</g>\n<!-- 113 -->\n<g id=\"node114\" class=\"node\">\n<title>113</title>\n<path fill=\"#eda673\" stroke=\"#000000\" d=\"M8057.5,-216C8057.5,-216 7930.5,-216 7930.5,-216 7924.5,-216 7918.5,-210 7918.5,-204 7918.5,-204 7918.5,-175 7918.5,-175 7918.5,-169 7924.5,-163 7930.5,-163 7930.5,-163 8057.5,-163 8057.5,-163 8063.5,-163 8069.5,-169 8069.5,-175 8069.5,-175 8069.5,-204 8069.5,-204 8069.5,-210 8063.5,-216 8057.5,-216\"/>\n<text text-anchor=\"middle\" x=\"7994\" y=\"-200.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">hour_of_day &lt;= 15.5</text>\n<text text-anchor=\"middle\" x=\"7994\" y=\"-185.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 16.9%</text>\n<text text-anchor=\"middle\" x=\"7994\" y=\"-170.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 229.2</text>\n</g>\n<!-- 112&#45;&gt;113 -->\n<g id=\"edge113\" class=\"edge\">\n<title>112&#45;&gt;113</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7994,-251.7971C7994,-243.7887 7994,-234.8597 7994,-226.3198\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7997.5001,-226.1841 7994,-216.1841 7990.5001,-226.1841 7997.5001,-226.1841\"/>\n</g>\n<!-- 120 -->\n<g id=\"node121\" class=\"node\">\n<title>120</title>\n<path fill=\"#f6d3ba\" stroke=\"#000000\" d=\"M8442.5,-216C8442.5,-216 8315.5,-216 8315.5,-216 8309.5,-216 8303.5,-210 8303.5,-204 8303.5,-204 8303.5,-175 8303.5,-175 8303.5,-169 8309.5,-163 8315.5,-163 8315.5,-163 8442.5,-163 8442.5,-163 8448.5,-163 8454.5,-169 8454.5,-175 8454.5,-175 8454.5,-204 8454.5,-204 8454.5,-210 8448.5,-216 8442.5,-216\"/>\n<text text-anchor=\"middle\" x=\"8379\" y=\"-200.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">hour_of_day &lt;= 21.5</text>\n<text text-anchor=\"middle\" x=\"8379\" y=\"-185.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 3.4%</text>\n<text text-anchor=\"middle\" x=\"8379\" y=\"-170.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 17.2</text>\n</g>\n<!-- 112&#45;&gt;120 -->\n<g id=\"edge120\" class=\"edge\">\n<title>112&#45;&gt;120</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M8069.6042,-261.0227C8133.8635,-246.1679 8226.092,-224.8476 8293.1235,-209.352\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"8294.2855,-212.6757 8303.2402,-207.0133 8292.7088,-205.8556 8294.2855,-212.6757\"/>\n</g>\n<!-- 114 -->\n<g id=\"node115\" class=\"node\">\n<title>114</title>\n<path fill=\"#f0b48a\" stroke=\"#000000\" d=\"M7974,-127C7974,-127 7844,-127 7844,-127 7838,-127 7832,-121 7832,-115 7832,-115 7832,-86 7832,-86 7832,-80 7838,-74 7844,-74 7844,-74 7974,-74 7974,-74 7980,-74 7986,-80 7986,-86 7986,-86 7986,-115 7986,-115 7986,-121 7980,-127 7974,-127\"/>\n<text text-anchor=\"middle\" x=\"7909\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">is_workingday &lt;= 0.5</text>\n<text text-anchor=\"middle\" x=\"7909\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 10.2%</text>\n<text text-anchor=\"middle\" x=\"7909\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 160.4</text>\n</g>\n<!-- 113&#45;&gt;114 -->\n<g id=\"edge114\" class=\"edge\">\n<title>113&#45;&gt;114</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7968.4972,-162.7971C7960.0083,-153.9087 7950.4362,-143.8862 7941.4913,-134.5203\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7943.9226,-131.9985 7934.4848,-127.1841 7938.8604,-136.8332 7943.9226,-131.9985\"/>\n</g>\n<!-- 117 -->\n<g id=\"node118\" class=\"node\">\n<title>117</title>\n<path fill=\"#e89050\" stroke=\"#000000\" d=\"M8143.5,-127C8143.5,-127 8016.5,-127 8016.5,-127 8010.5,-127 8004.5,-121 8004.5,-115 8004.5,-115 8004.5,-86 8004.5,-86 8004.5,-80 8010.5,-74 8016.5,-74 8016.5,-74 8143.5,-74 8143.5,-74 8149.5,-74 8155.5,-80 8155.5,-86 8155.5,-86 8155.5,-115 8155.5,-115 8155.5,-121 8149.5,-127 8143.5,-127\"/>\n<text text-anchor=\"middle\" x=\"8080\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">hour_of_day &lt;= 18.5</text>\n<text text-anchor=\"middle\" x=\"8080\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 6.7%</text>\n<text text-anchor=\"middle\" x=\"8080\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 333.0</text>\n</g>\n<!-- 113&#45;&gt;117 -->\n<g id=\"edge117\" class=\"edge\">\n<title>113&#45;&gt;117</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M8019.8028,-162.7971C8028.3916,-153.9087 8038.0763,-143.8862 8047.1264,-134.5203\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"8049.7835,-136.8074 8054.2154,-127.1841 8044.7496,-131.9432 8049.7835,-136.8074\"/>\n</g>\n<!-- 115 -->\n<g id=\"node116\" class=\"node\">\n<title>115</title>\n<path fill=\"#eca571\" stroke=\"#000000\" d=\"M7836,-38C7836,-38 7740,-38 7740,-38 7734,-38 7728,-32 7728,-26 7728,-26 7728,-12 7728,-12 7728,-6 7734,0 7740,0 7740,0 7836,0 7836,0 7842,0 7848,-6 7848,-12 7848,-12 7848,-26 7848,-26 7848,-32 7842,-38 7836,-38\"/>\n<text text-anchor=\"middle\" x=\"7788\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 3.1%</text>\n<text text-anchor=\"middle\" x=\"7788\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 234.6</text>\n</g>\n<!-- 114&#45;&gt;115 -->\n<g id=\"edge115\" class=\"edge\">\n<title>114&#45;&gt;115</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7869.3801,-73.8139C7855.1108,-64.2027 7839.0752,-53.4019 7825.0349,-43.945\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7826.8337,-40.9367 7816.5843,-38.2531 7822.9231,-46.7425 7826.8337,-40.9367\"/>\n</g>\n<!-- 116 -->\n<g id=\"node117\" class=\"node\">\n<title>116</title>\n<path fill=\"#f1bb95\" stroke=\"#000000\" d=\"M7974,-38C7974,-38 7878,-38 7878,-38 7872,-38 7866,-32 7866,-26 7866,-26 7866,-12 7866,-12 7866,-6 7872,0 7878,0 7878,0 7974,0 7974,0 7980,0 7986,-6 7986,-12 7986,-12 7986,-26 7986,-26 7986,-32 7980,-38 7974,-38\"/>\n<text text-anchor=\"middle\" x=\"7926\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 7.0%</text>\n<text text-anchor=\"middle\" x=\"7926\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 127.2</text>\n</g>\n<!-- 114&#45;&gt;116 -->\n<g id=\"edge116\" class=\"edge\">\n<title>114&#45;&gt;116</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M7914.5664,-73.8139C7916.2686,-65.6535 7918.1497,-56.6354 7919.8861,-48.3105\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"7923.3683,-48.7571 7921.984,-38.2531 7916.5157,-47.3277 7923.3683,-48.7571\"/>\n</g>\n<!-- 118 -->\n<g id=\"node119\" class=\"node\">\n<title>118</title>\n<path fill=\"#e58139\" stroke=\"#000000\" d=\"M8112,-38C8112,-38 8016,-38 8016,-38 8010,-38 8004,-32 8004,-26 8004,-26 8004,-12 8004,-12 8004,-6 8010,0 8016,0 8016,0 8112,0 8112,0 8118,0 8124,-6 8124,-12 8124,-12 8124,-26 8124,-26 8124,-32 8118,-38 8112,-38\"/>\n<text text-anchor=\"middle\" x=\"8064\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 4.2%</text>\n<text text-anchor=\"middle\" x=\"8064\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 401.3</text>\n</g>\n<!-- 117&#45;&gt;118 -->\n<g id=\"edge118\" class=\"edge\">\n<title>117&#45;&gt;118</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M8074.761,-73.8139C8073.159,-65.6535 8071.3886,-56.6354 8069.7542,-48.3105\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"8073.1407,-47.3915 8067.7797,-38.2531 8066.2718,-48.74 8073.1407,-47.3915\"/>\n</g>\n<!-- 119 -->\n<g id=\"node120\" class=\"node\">\n<title>119</title>\n<path fill=\"#eda775\" stroke=\"#000000\" d=\"M8250,-38C8250,-38 8154,-38 8154,-38 8148,-38 8142,-32 8142,-26 8142,-26 8142,-12 8142,-12 8142,-6 8148,0 8154,0 8154,0 8250,0 8250,0 8256,0 8262,-6 8262,-12 8262,-12 8262,-26 8262,-26 8262,-32 8256,-38 8250,-38\"/>\n<text text-anchor=\"middle\" x=\"8202\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 2.6%</text>\n<text text-anchor=\"middle\" x=\"8202\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 223.7</text>\n</g>\n<!-- 117&#45;&gt;119 -->\n<g id=\"edge119\" class=\"edge\">\n<title>117&#45;&gt;119</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M8119.9474,-73.8139C8134.3346,-64.2027 8150.5026,-53.4019 8164.659,-43.945\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"8166.8084,-46.7183 8173.1795,-38.2531 8162.92,-40.8976 8166.8084,-46.7183\"/>\n</g>\n<!-- 121 -->\n<g id=\"node122\" class=\"node\">\n<title>121</title>\n<path fill=\"#f3c6a6\" stroke=\"#000000\" d=\"M8471,-127C8471,-127 8287,-127 8287,-127 8281,-127 8275,-121 8275,-115 8275,-115 8275,-86 8275,-86 8275,-80 8281,-74 8287,-74 8287,-74 8471,-74 8471,-74 8477,-74 8483,-80 8483,-86 8483,-86 8483,-115 8483,-115 8483,-121 8477,-127 8471,-127\"/>\n<text text-anchor=\"middle\" x=\"8379\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">feels_like_temperature &lt;= 0.6</text>\n<text text-anchor=\"middle\" x=\"8379\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 1.2%</text>\n<text text-anchor=\"middle\" x=\"8379\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 77.1</text>\n</g>\n<!-- 120&#45;&gt;121 -->\n<g id=\"edge121\" class=\"edge\">\n<title>120&#45;&gt;121</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M8379,-162.7971C8379,-154.7887 8379,-145.8597 8379,-137.3198\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"8382.5001,-137.1841 8379,-127.1841 8375.5001,-137.1841 8382.5001,-137.1841\"/>\n</g>\n<!-- 124 -->\n<g id=\"node125\" class=\"node\">\n<title>124</title>\n<path fill=\"#f7dac5\" stroke=\"#000000\" d=\"M8679.5,-127C8679.5,-127 8552.5,-127 8552.5,-127 8546.5,-127 8540.5,-121 8540.5,-115 8540.5,-115 8540.5,-86 8540.5,-86 8540.5,-80 8546.5,-74 8552.5,-74 8552.5,-74 8679.5,-74 8679.5,-74 8685.5,-74 8691.5,-80 8691.5,-86 8691.5,-86 8691.5,-115 8691.5,-115 8691.5,-121 8685.5,-127 8679.5,-127\"/>\n<text text-anchor=\"middle\" x=\"8616\" y=\"-111.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">hour_of_day &lt;= 22.5</text>\n<text text-anchor=\"middle\" x=\"8616\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 2.2%</text>\n<text text-anchor=\"middle\" x=\"8616\" y=\"-81.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;14.8</text>\n</g>\n<!-- 120&#45;&gt;124 -->\n<g id=\"edge124\" class=\"edge\">\n<title>120&#45;&gt;124</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M8449.7868,-162.9176C8476.7516,-152.7916 8507.6733,-141.1797 8535.4762,-130.7389\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"8537.0375,-133.8913 8545.1687,-127.0991 8534.5766,-127.3381 8537.0375,-133.8913\"/>\n</g>\n<!-- 122 -->\n<g id=\"node123\" class=\"node\">\n<title>122</title>\n<path fill=\"#f5d0b4\" stroke=\"#000000\" d=\"M8388,-38C8388,-38 8292,-38 8292,-38 8286,-38 8280,-32 8280,-26 8280,-26 8280,-12 8280,-12 8280,-6 8286,0 8292,0 8292,0 8388,0 8388,0 8394,0 8400,-6 8400,-12 8400,-12 8400,-26 8400,-26 8400,-32 8394,-38 8388,-38\"/>\n<text text-anchor=\"middle\" x=\"8340\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.4%</text>\n<text text-anchor=\"middle\" x=\"8340\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 33.2</text>\n</g>\n<!-- 121&#45;&gt;122 -->\n<g id=\"edge122\" class=\"edge\">\n<title>121&#45;&gt;122</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M8366.2299,-73.8139C8362.1948,-65.3815 8357.7214,-56.0333 8353.6287,-47.4804\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"8356.6868,-45.7627 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          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UDhu91aa8vuw"
      },
      "source": [
        "# Inference"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EiQwrb7TK40n",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 437
        },
        "outputId": "cff68332-3203-4585-8dbc-9b12688035b5"
      },
      "source": [
        "test_predictions = X_test.copy()\n",
        "# real output (rented_bikes) from test dataset\n",
        "test_predictions[\"rented_bikes\"] = y_test\n",
        "\n",
        "# add \"predicted_rented_bikes\" from test dataset\n",
        "test_predictions[\"predicted_rented_bikes\"] = best_model.predict(X_test).astype(int)\n",
        "\n",
        "# show results\n",
        "test_predictions"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>season</th>\n",
              "      <th>year</th>\n",
              "      <th>month</th>\n",
              "      <th>hour_of_day</th>\n",
              "      <th>is_holiday</th>\n",
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              "      <th>feels_like_temperature</th>\n",
              "      <th>humidity</th>\n",
              "      <th>windspeed</th>\n",
              "      <th>rented_bikes</th>\n",
              "      <th>predicted_rented_bikes</th>\n",
              "    </tr>\n",
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              "  <tbody>\n",
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              "      <th>12830</th>\n",
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              "      <td>0</td>\n",
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              "      <td>0.26</td>\n",
              "      <td>0.2273</td>\n",
              "      <td>0.56</td>\n",
              "      <td>0.3881</td>\n",
              "      <td>13</td>\n",
              "      <td>10</td>\n",
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              "      <td>1</td>\n",
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              "      <td>0.16</td>\n",
              "      <td>0.1818</td>\n",
              "      <td>0.86</td>\n",
              "      <td>0.1045</td>\n",
              "      <td>72</td>\n",
              "      <td>74</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5214 rows × 14 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       season  year  month  ...  windspeed  rented_bikes  predicted_rented_bikes\n",
              "12830       3     1      6  ...     0.1940           425                     397\n",
              "8688        1     1      1  ...     0.2239            88                      99\n",
              "7091        4     0     10  ...     0.2836             4                      13\n",
              "12230       2     1      5  ...     0.3582           526                     564\n",
              "431         1     0      1  ...     0.3881            13                      10\n",
              "...       ...   ...    ...  ...        ...           ...                     ...\n",
              "12749       2     1      6  ...     0.1343           167                     182\n",
              "11476       2     1      4  ...     0.0000           214                     241\n",
              "12847       3     1      6  ...     0.2239           556                     555\n",
              "16721       4     1     12  ...     0.1940           312                     297\n",
              "9511        1     1      2  ...     0.1045            72                      74\n",
              "\n",
              "[5214 rows x 14 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SwfQEr_NGlDa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 911
        },
        "outputId": "0eadcb49-934b-49bd-fa70-15795528d98a"
      },
      "source": [
        "# plot truth vs prediction values\n",
        "test_predictions.plot(\n",
        "    kind=\"scatter\",\n",
        "    x=\"rented_bikes\",\n",
        "    y=\"predicted_rented_bikes\",\n",
        "    title=\"Rented bikes vs predicted rented bikes\",\n",
        "    figsize=(15, 15),\n",
        ")"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f79d0786e90>"
            ]
          },
          "metadata": {},
          "execution_count": 27
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x1080 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n76_rUaul1oA"
      },
      "source": [
        "# Model Serving\n",
        "\n",
        "Reference: https://www.mlflow.org/docs/latest/models.html"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gIp8mJHXNbJR"
      },
      "source": [
        "get_ipython().system_raw(f\"mlflow models serve --model-uri {best_model_uri} --host 0.0.0.0 --port 5001 --workers 1 --no-conda &\")\n",
        "!sleep 5"
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qJlIxKfGzQC5"
      },
      "source": [
        "# alternative method\n",
        "# import mlflow.models.cli\n",
        "# mlflow.models.cli.serve([\"--model-uri\", best_model_uri, \"--no-conda\", \"--host\", \"0.0.0.0\", \"--port\", 5005, \"--workers\", 1])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "U5cDsIzuU5rO"
      },
      "source": [
        "### REST API request"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8D_kKKrgPVBb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "159eb8a4-5046-4a14-93e6-94ea6c12a38b"
      },
      "source": [
        "%%bash\n",
        "curl --silent --show-error 'http://localhost:5001/invocations' -H 'Content-Type: application/json' -d '{\n",
        "    \"columns\": [\"season\", \"year\", \"month\", \"hour_of_day\", \"is_holiday\", \"weekday\", \"is_workingday\", \"weather_situation\", \"temperature\", \"feels_like_temperature\", \"humidity\", \"windspeed\"],\n",
        "    \"data\": [[1, 0, 1, 0, 0, 6, 0, 1, 0.24, 0.2879, 0.81, 0.0000]]\n",
        "}'"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[35.616200948055564]"
          ]
        }
      ]
    }
  ]
}