MLflow-example-notebook.ipynb

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      "name": "MLflow-example-notebook.ipynb",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/alfozan/mlflow-example/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",
        "outputId": "6a47110e-5994-4d05-e380-58540915e624",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        }
      },
      "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": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[K     |████████████████████████████████| 13.9MB 299kB/s \n",
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            "\u001b[K     |████████████████████████████████| 51kB 4.5MB/s \n",
            "\u001b[?25h  Building wheel for querystring-parser (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for databricks-cli (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for prometheus-flask-exporter (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for alembic (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for sqlalchemy (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "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": {
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        "outputId": "2dad51e5-5194-44af-c06c-5481c81d7639",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 276
        }
      },
      "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": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2020-10-20 11:27:34--  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   470KB/s    in 0.6s    \n",
            "\n",
            "2020-10-20 11:27:35 (470 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"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mFGzYdKCCNiK",
        "outputId": "8783bf81-d46a-4958-d2dc-59a324868a64",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        }
      },
      "source": [
        "# load input data into pandas dataframe\n",
        "bike_sharing = pd.read_csv(\"hour.csv\")\n",
        "bike_sharing        "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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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",
              "      <th>mnth</th>\n",
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              "      <th>holiday</th>\n",
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              "      <th>atemp</th>\n",
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              "      <th>windspeed</th>\n",
              "      <th>casual</th>\n",
              "      <th>registered</th>\n",
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              "      <th>17374</th>\n",
              "      <td>17375</td>\n",
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              "      <td>12</td>\n",
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              "      <td>0.26</td>\n",
              "      <td>0.2576</td>\n",
              "      <td>0.60</td>\n",
              "      <td>0.1642</td>\n",
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              "      <td>83</td>\n",
              "      <td>90</td>\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",
              "      <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",
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              "      <td>48</td>\n",
              "      <td>61</td>\n",
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              "    <tr>\n",
              "      <th>17378</th>\n",
              "      <td>17379</td>\n",
              "      <td>2012-12-31</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>12</td>\n",
              "      <td>23</td>\n",
              "      <td>0</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]"
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          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fQk3RQt2FB8x"
      },
      "source": [
        "## Data preprocessing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vyS5Ru5aE5Y7",
        "outputId": "5d0b2528-9664-437d-8e3f-61119fdaad5e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        }
      },
      "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": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <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",
              "      <th>weekday</th>\n",
              "      <th>is_workingday</th>\n",
              "      <th>weather_situation</th>\n",
              "      <th>temperature</th>\n",
              "      <th>feels_like_temperature</th>\n",
              "      <th>humidity</th>\n",
              "      <th>windspeed</th>\n",
              "      <th>rented_bikes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</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>0.81</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": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "40MGTHbNFKTP"
      },
      "source": [
        "### Data Visualization "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bNZOegwGHzUR",
        "outputId": "45a00d75-c019-4c39-96c4-08e3995fb381",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 639
        }
      },
      "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": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7ffa1bc83a20>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZMg_JKoUKq9j"
      },
      "source": [
        "## Prepare training and test data sets\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZwtDgaZ9Ktie",
        "outputId": "4971f3d6-5e99-4583-acb6-4ef73892a633",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "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": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Training samples: 145980\n",
            "Test samples: 62568\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "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": null,
      "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": null,
      "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": null,
      "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": null,
      "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": null,
      "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": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vGmHvdrMw_-U"
      },
      "source": [
        "## Initialize MLflow experiment"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "noNeZRbU_llh",
        "outputId": "ccccc65c-c900-4950-dafe-c8cde3ac318f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "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": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "INFO: 'rented_bikes' does not exist. Creating a new experiment\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "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": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "P8cfq8bO_LRr"
      },
      "source": [
        "### MLflow UI URL"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4h3bKHMYUIG6",
        "outputId": "568c534b-01fc-4a5c-a3c1-8ff583588385",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "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": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "  Building wheel for pyngrok (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "MLflow Tracking UI: https://0a4aa47d9c97.ngrok.io\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "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": null,
      "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": null,
      "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": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u23-Tpn_0X7d"
      },
      "source": [
        "## Training runs"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Le6sa7jjg37v",
        "outputId": "7e8c3e45-e75a-45ce-8157-38b097d623cc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 639
        }
      },
      "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": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Run 0: {'learning_rate': 0.1, 'max_depth': 4}\n",
            "RMSE score: 51.9849\n",
            "Cross-Validation RMSE score: 56.5460 (std = 0.1544)\n",
            "\n",
            "Run 1: {'learning_rate': 0.1, 'max_depth': 5}\n",
            "RMSE score: 44.7164\n",
            "Cross-Validation RMSE score: 48.1749 (std = 0.1554)\n",
            "\n",
            "Run 2: {'learning_rate': 0.1, 'max_depth': 6}\n",
            "RMSE score: 41.8975\n",
            "Cross-Validation RMSE score: 44.9725 (std = 0.4530)\n",
            "\n",
            "Run 3: {'learning_rate': 0.05, 'max_depth': 4}\n",
            "RMSE score: 63.1546\n",
            "Cross-Validation RMSE score: 67.8220 (std = 1.7218)\n",
            "\n",
            "Run 4: {'learning_rate': 0.05, 'max_depth': 5}\n",
            "RMSE score: 53.0479\n",
            "Cross-Validation RMSE score: 55.9807 (std = 0.8559)\n",
            "\n",
            "Run 5: {'learning_rate': 0.05, 'max_depth': 6}\n",
            "RMSE score: 46.2891\n",
            "Cross-Validation RMSE score: 49.8140 (std = 0.5416)\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: 112.4921\n",
            "Cross-Validation RMSE score: 116.0879 (std = 0.9958)\n",
            "\n",
            "Run 8: {'learning_rate': 0.01, 'max_depth': 6}\n",
            "RMSE score: 106.2637\n",
            "Cross-Validation RMSE score: 109.3515 (std = 1.2056)\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "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": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wHVM74A--4-C",
        "outputId": "b28470ff-aa99-4f19-c124-d4b9c3a88233",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 104
        }
      },
      "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": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Best run info:\n",
            "Run id: 4a1efaa6e70047fb898dad053ddb2e85\n",
            "Run parameters: {'learning_rate': '0.1', 'max_depth': '6'}\n",
            "Run score: RMSE_CV = 44.9725\n",
            "Run model URI: file:///content/mlruns/1/4a1efaa6e70047fb898dad053ddb2e85/artifacts/model\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WmjSO3vhCP7u",
        "outputId": "52e2c4ac-4aeb-44b8-d65d-7d2de8122fb8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        }
      },
      "source": [
        "model_feature_importance(best_model)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LQRJKFuJCSBZ",
        "outputId": "3a60cd14-f402-4304-ee8c-7f3647be4721",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 496
        }
      },
      "source": [
        "model_permutation_importance(best_model)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fR2F0ex7CS4I",
        "outputId": "ff25041b-c91e-4372-ab49-514e350bc709",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 815
        }
      },
      "source": [
        "model_tree_visualization(best_model)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<graphviz.files.Source at 0x7ffa18108e48>"
            ],
            "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=\"M3671,-305C3671,-305 3487,-305 3487,-305 3481,-305 3475,-299 3475,-293 3475,-293 3475,-264 3475,-264 3475,-258 3481,-252 3487,-252 3487,-252 3671,-252 3671,-252 3677,-252 3683,-258 3683,-264 3683,-264 3683,-293 3683,-293 3683,-299 3677,-305 3671,-305\"/>\n<text text-anchor=\"middle\" x=\"3579\" y=\"-289.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">feels_like_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,-342.5902C3413.3379,-331.92 3452.2497,-319.3724 3486.8302,-308.2214\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"3488.0171,-311.5162 3496.4604,-305.116 3485.8688,-304.854 3488.0171,-311.5162\"/>\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 3086,-169 3086,-175 3086,-175 3086,-204 3086,-204 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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\" d=\"M2360.8136,-73.8139C2344.2325,-64.0214 2325.5603,-52.9939 2309.3342,-43.4112\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"2310.9906,-40.3246 2300.6003,-38.2531 2307.431,-46.352 2310.9906,-40.3246\"/>\n</g>\n<!-- 38 -->\n<g id=\"node39\" class=\"node\">\n<title>38</title>\n<path fill=\"#fffefe\" stroke=\"#000000\" d=\"M2454,-38C2454,-38 2358,-38 2358,-38 2352,-38 2346,-32 2346,-26 2346,-26 2346,-12 2346,-12 2346,-6 2352,0 2358,0 2358,0 2454,0 2454,0 2460,0 2466,-6 2466,-12 2466,-12 2466,-26 2466,-26 2466,-32 2460,-38 2454,-38\"/>\n<text text-anchor=\"middle\" x=\"2406\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.1%</text>\n<text text-anchor=\"middle\" x=\"2406\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;186.6</text>\n</g>\n<!-- 36&#45;&gt;38 -->\n<g id=\"edge38\" class=\"edge\">\n<title>36&#45;&gt;38</title>\n<path fill=\"none\" stroke=\"#000000\" 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d=\"M2590.4068,-73.8139C2582.8839,-64.9281 2574.5001,-55.0255 2566.9504,-46.1081\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"2569.4329,-43.6236 2560.3001,-38.2531 2564.0905,-48.1467 2569.4329,-43.6236\"/>\n</g>\n<!-- 41 -->\n<g id=\"node42\" class=\"node\">\n<title>41</title>\n<path fill=\"#fffefd\" stroke=\"#000000\" d=\"M2730,-38C2730,-38 2634,-38 2634,-38 2628,-38 2622,-32 2622,-26 2622,-26 2622,-12 2622,-12 2622,-6 2628,0 2634,0 2634,0 2730,0 2730,0 2736,0 2742,-6 2742,-12 2742,-12 2742,-26 2742,-26 2742,-32 2736,-38 2730,-38\"/>\n<text text-anchor=\"middle\" x=\"2682\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.1%</text>\n<text text-anchor=\"middle\" x=\"2682\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = &#45;182.2</text>\n</g>\n<!-- 39&#45;&gt;41 -->\n<g id=\"edge41\" class=\"edge\">\n<title>39&#45;&gt;41</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 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8349.2131,-38.2531 8350.3725,-48.7843 8356.6868,-45.7627\"/>\n</g>\n<!-- 123 -->\n<g id=\"node124\" class=\"node\">\n<title>123</title>\n<path fill=\"#f2c29f\" stroke=\"#000000\" d=\"M8526,-38C8526,-38 8430,-38 8430,-38 8424,-38 8418,-32 8418,-26 8418,-26 8418,-12 8418,-12 8418,-6 8424,0 8430,0 8430,0 8526,0 8526,0 8532,0 8538,-6 8538,-12 8538,-12 8538,-26 8538,-26 8538,-32 8532,-38 8526,-38\"/>\n<text text-anchor=\"middle\" x=\"8478\" y=\"-22.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">samples = 0.8%</text>\n<text text-anchor=\"middle\" x=\"8478\" y=\"-7.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\" fill=\"#000000\">value = 98.3</text>\n</g>\n<!-- 121&#45;&gt;123 -->\n<g id=\"edge123\" class=\"edge\">\n<title>121&#45;&gt;123</title>\n<path fill=\"none\" stroke=\"#000000\" d=\"M8411.4163,-73.8139C8422.7607,-64.4747 8435.4697,-54.0123 8446.7195,-44.7511\"/>\n<polygon fill=\"#000000\" stroke=\"#000000\" points=\"8449.1169,-47.311 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          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UDhu91aa8vuw"
      },
      "source": [
        "# Inference"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EiQwrb7TK40n",
        "outputId": "709d749f-bc0d-4b68-c2c4-8c1a0197eca6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        }
      },
      "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": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <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>humidity</th>\n",
              "      <th>windspeed</th>\n",
              "      <th>rented_bikes</th>\n",
              "      <th>predicted_rented_bikes</th>\n",
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              "      <th>12830</th>\n",
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              "      <td>0.56</td>\n",
              "      <td>0.3881</td>\n",
              "      <td>13</td>\n",
              "      <td>10</td>\n",
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              "      <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": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SwfQEr_NGlDa",
        "outputId": "e153d67b-b13f-4b13-bbe9-542eed7442a8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 911
        }
      },
      "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": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7ffa18b8aa20>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x1080 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "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": null,
      "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",
        "outputId": "ffa97db8-1e52-4bd6-f2e4-fe16efec6d86",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "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": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[35.6162009480556]"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}