GeoAI_cropland_mapping_Best_Submission.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p_oKrnWWjNoK"
      },
      "source": [
        "## **Imports**"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "This section is dedicated to importing/installing the necessary libraies and dependencies."
      ],
      "metadata": {
        "id": "0APvamC1W9Hf"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ch636sanjHsk",
        "outputId": "1910c1ae-d7be-4eb8-ea85-a64382f130e6"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting optuna\n",
            "  Downloading optuna-3.3.0-py3-none-any.whl (404 kB)\n",
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            "\u001b[?25hCollecting alembic>=1.5.0 (from optuna)\n",
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            "Collecting Mako (from alembic>=1.5.0->optuna)\n",
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            "Installing collected packages: Mako, colorlog, cmaes, alembic, optuna\n",
            "Successfully installed Mako-1.2.4 alembic-1.12.0 cmaes-0.10.0 colorlog-6.7.0 optuna-3.3.0\n"
          ]
        }
      ],
      "source": [
        "!pip install optuna"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5F3tAjidjRNj",
        "outputId": "3171dd0c-21f6-46a6-c119-8fd976813a30"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-2-e1e41ffbd967>:16: MatplotlibDeprecationWarning: The seaborn styles shipped by Matplotlib are deprecated since 3.6, as they no longer correspond to the styles shipped by seaborn. However, they will remain available as 'seaborn-v0_8-<style>'. Alternatively, directly use the seaborn API instead.\n",
            "  mpl.style.use('seaborn')\n"
          ]
        }
      ],
      "source": [
        "import warnings\n",
        "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
        "\n",
        "import ee\n",
        "from google.colab import files\n",
        "import glob\n",
        "\n",
        "import pandas as pd\n",
        "import copy\n",
        "import numpy as np\n",
        "import tqdm\n",
        "from sklearn.model_selection import StratifiedKFold, train_test_split\n",
        "import random\n",
        "import matplotlib as mpl\n",
        "import matplotlib.pyplot as plt\n",
        "mpl.style.use('seaborn')\n",
        "import seaborn as sns\n",
        "\n",
        "from functools import reduce\n",
        "from tqdm.notebook import tqdm\n",
        "import scipy as sp\n",
        "from sklearn.utils import shuffle\n",
        "\n",
        "#importing all the required ML packages\n",
        "from sklearn.decomposition import PCA\n",
        "from sklearn.feature_selection import RFE\n",
        "\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis, QuadraticDiscriminantAnalysis\n",
        "from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier, GradientBoostingClassifier, BaggingClassifier\n",
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "from sklearn.tree import DecisionTreeClassifier\n",
        "from lightgbm import LGBMClassifier, plot_importance\n",
        "from xgboost import XGBClassifier\n",
        "from sklearn.model_selection import train_test_split, cross_val_score, StratifiedKFold, RandomizedSearchCV, RepeatedStratifiedKFold, KFold\n",
        "from sklearn.metrics import accuracy_score, log_loss,  classification_report, make_scorer, confusion_matrix, roc_auc_score\n",
        "from sklearn.ensemble import VotingClassifier\n",
        "\n",
        "import optuna\n",
        "\n",
        "# Pytorch\n",
        "import torch\n",
        "from torch.utils.data import DataLoader, TensorDataset\n",
        "import torch.nn as nn\n",
        "import torch.optim as optim"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "uiyji72ejUOz"
      },
      "outputs": [],
      "source": [
        "# Set seed for reproducability\n",
        "SEED = 2023\n",
        "random.seed(SEED)\n",
        "np.random.seed(SEED)\n",
        "n_jobs = -1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kAppDzHpjXYe",
        "outputId": "3963683e-7bbf-48dd-c375-6de24471b848"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2_ePzU9LjmJ7"
      },
      "source": [
        "##**S2 Dataset Preparation**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p29O83kEjnp8",
        "outputId": "961f408a-6216-48a4-fde8-9efe4fcf7371"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "To authorize access needed by Earth Engine, open the following URL in a web browser and follow the instructions. If the web browser does not start automatically, please manually browse the URL below.\n",
            "\n",
            "    https://code.earthengine.google.com/client-auth?scopes=https%3A//www.googleapis.com/auth/earthengine%20https%3A//www.googleapis.com/auth/devstorage.full_control&request_id=HhshyhAdpgV--L8TdWAJm8Yd8I8mVfmjFC1N_tGngV0&tc=QST91gf-osYoIkvy1hUMMyLvOcxyuZ4IW1zaMGgsZzI&cc=JSWWvRxKGA0C6DO2Ra4xRLohzcSkSUEiv3KMnIImLcM\n",
            "\n",
            "The authorization workflow will generate a code, which you should paste in the box below.\n",
            "Enter verification code: 4/1AfJohXl45G1eBo4WcaIKVEZvf27DdS684GUUAVXubxEGf4hJebbIFjqTI-s\n",
            "\n",
            "Successfully saved authorization token.\n"
          ]
        }
      ],
      "source": [
        "# Get authetication token and sign in to Google Earth Engine\n",
        "ee.Authenticate()\n",
        "ee.Initialize()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "um9hDqytj1wY"
      },
      "outputs": [],
      "source": [
        "## Upload the train and test csv provided by the competition\n",
        "train_coords_df = pd.read_csv('Train.csv')\n",
        "test_coords_df = pd.read_csv('Test.csv')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "XYu6_iCnj8ND",
        "outputId": "4733ca90-0070-4698-b364-2d820192cc87"
      },
      "outputs": [
        {
          "output_type": "execute_result",
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              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-6333017c-6ee4-45c0-875f-5121f3b7acfb button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ],
      "source": [
        "train_coords_df.head() # len = 500"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "KpSXAOVZj_O_",
        "outputId": "ff5dd669-a2c3-4d7d-af47-87ca379dd3ec"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                ID        Lat        Lon\n",
              "0  ID_9ZLHTVF6NSU7  34.254835  70.348699\n",
              "1  ID_LNN7BFCVEZKA  32.009669  48.535526\n",
              "2  ID_SOYSG7W04UH3  14.431884  33.399991\n",
              "3  ID_EAP7EXXV8ZDE  14.281866  33.441224\n",
              "4  ID_QPRX1TUQVGHU  14.399365  33.109566"
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              "        document.querySelector('#df-f7d22400-b6a1-41c5-b21d-25a9c94eddf0 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-f7d22400-b6a1-41c5-b21d-25a9c94eddf0');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
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              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
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              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "source": [
        "test_coords_df.head() # len = 500"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "_ZipsuYdkHwg"
      },
      "outputs": [],
      "source": [
        "# Function to differentiate the country based on latitude and longitude\n",
        "def get_country(latitude, longitude):\n",
        "    if latitude > 30 and latitude < 40 and longitude > 60 and longitude < 80:\n",
        "        return 'Afghanistan'\n",
        "    elif latitude > 30 and latitude < 40 and longitude > 45 and longitude < 65:\n",
        "        return 'Iran'\n",
        "    elif latitude > 10 and latitude < 20 and longitude > 20 and longitude < 40:\n",
        "        return 'Sudan'\n",
        "    else:\n",
        "        return 'Unknown'\n",
        "\n",
        "# Apply the function to create a new column\n",
        "train_coords_df['Country'] = train_coords_df.apply(lambda row: get_country(row['Lat'], row['Lon']), axis=1)\n",
        "test_coords_df['Country'] = test_coords_df.apply(lambda row: get_country(row['Lat'], row['Lon']), axis=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "i0pghFwJkM_Z",
        "outputId": "5130003c-2844-437f-9349-78680f87aa45"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   ID        Lat        Lon  Target      Country\n",
              "0     ID_SJ098E7S2SY9  34.162491  70.763668       0  Afghanistan\n",
              "1     ID_CWCD60FGJJYY  32.075695  48.492047       0         Iran\n",
              "2     ID_R1XF70RMVGL3  14.542826  33.313483       1        Sudan\n",
              "3     ID_0ZBIDY0PEBVO  14.359480  33.284108       1        Sudan\n",
              "4     ID_C20R2C0AYIT0  14.419128  33.528450       0        Sudan\n",
              "...               ...        ...        ...     ...          ...\n",
              "1495  ID_T3WAJGS3B84X  34.292702  70.404578       0  Afghanistan\n",
              "1496  ID_Q31SWRW623Y8  32.105698  48.294867       1         Iran\n",
              "1497  ID_O2KBC7HPNOAQ  32.235685  48.185542       0         Iran\n",
              "1498  ID_8VNTHGHLSUNI  14.329207  33.253206       0        Sudan\n",
              "1499  ID_C5ACHNL98VTX  14.179817  33.179275       0        Sudan\n",
              "\n",
              "[1500 rows x 5 columns]"
            ],
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              "      <td>0</td>\n",
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              "      <th>3</th>\n",
              "      <td>ID_0ZBIDY0PEBVO</td>\n",
              "      <td>14.359480</td>\n",
              "      <td>33.284108</td>\n",
              "      <td>1</td>\n",
              "      <td>Sudan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ID_C20R2C0AYIT0</td>\n",
              "      <td>14.419128</td>\n",
              "      <td>33.528450</td>\n",
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              "      <td>Sudan</td>\n",
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              "    <tr>\n",
              "      <th>1495</th>\n",
              "      <td>ID_T3WAJGS3B84X</td>\n",
              "      <td>34.292702</td>\n",
              "      <td>70.404578</td>\n",
              "      <td>0</td>\n",
              "      <td>Afghanistan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1496</th>\n",
              "      <td>ID_Q31SWRW623Y8</td>\n",
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              "      <td>48.294867</td>\n",
              "      <td>1</td>\n",
              "      <td>Iran</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1497</th>\n",
              "      <td>ID_O2KBC7HPNOAQ</td>\n",
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              "      <td>48.185542</td>\n",
              "      <td>0</td>\n",
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              "      <td>ID_8VNTHGHLSUNI</td>\n",
              "      <td>14.329207</td>\n",
              "      <td>33.253206</td>\n",
              "      <td>0</td>\n",
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              "      <td>14.179817</td>\n",
              "      <td>33.179275</td>\n",
              "      <td>0</td>\n",
              "      <td>Sudan</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "<p>1500 rows × 5 columns</p>\n",
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              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-6d4f3a8b-604a-4ef1-9a43-09c88cda087a button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-6d4f3a8b-604a-4ef1-9a43-09c88cda087a');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-6340ee91-ea1d-4863-8dc1-dc45fee13c8a\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-6340ee91-ea1d-4863-8dc1-dc45fee13c8a')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-6340ee91-ea1d-4863-8dc1-dc45fee13c8a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ],
      "source": [
        "train_coords_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "zjPcHRIFkOY7",
        "outputId": "fdf59b8a-fa7f-458c-8977-d6c842db7714"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   ID        Lat        Lon      Country\n",
              "0     ID_9ZLHTVF6NSU7  34.254835  70.348699  Afghanistan\n",
              "1     ID_LNN7BFCVEZKA  32.009669  48.535526         Iran\n",
              "2     ID_SOYSG7W04UH3  14.431884  33.399991        Sudan\n",
              "3     ID_EAP7EXXV8ZDE  14.281866  33.441224        Sudan\n",
              "4     ID_QPRX1TUQVGHU  14.399365  33.109566        Sudan\n",
              "...               ...        ...        ...          ...\n",
              "1495  ID_6LVHE89NN5VE  34.077906  70.697531  Afghanistan\n",
              "1496  ID_M51GDSUBKS8Q  32.202177  48.344005         Iran\n",
              "1497  ID_469MTLRKJC64  32.340069  48.157425         Iran\n",
              "1498  ID_DMH9P3N6O3DK  14.260575  33.551627        Sudan\n",
              "1499  ID_FKB2YZ2BXZ0Z  14.148376  33.371784        Sudan\n",
              "\n",
              "[1500 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-c17fd8f4-3a73-44c1-93be-53bfef525f2e\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ID</th>\n",
              "      <th>Lat</th>\n",
              "      <th>Lon</th>\n",
              "      <th>Country</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ID_9ZLHTVF6NSU7</td>\n",
              "      <td>34.254835</td>\n",
              "      <td>70.348699</td>\n",
              "      <td>Afghanistan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ID_LNN7BFCVEZKA</td>\n",
              "      <td>32.009669</td>\n",
              "      <td>48.535526</td>\n",
              "      <td>Iran</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ID_SOYSG7W04UH3</td>\n",
              "      <td>14.431884</td>\n",
              "      <td>33.399991</td>\n",
              "      <td>Sudan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ID_EAP7EXXV8ZDE</td>\n",
              "      <td>14.281866</td>\n",
              "      <td>33.441224</td>\n",
              "      <td>Sudan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ID_QPRX1TUQVGHU</td>\n",
              "      <td>14.399365</td>\n",
              "      <td>33.109566</td>\n",
              "      <td>Sudan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1495</th>\n",
              "      <td>ID_6LVHE89NN5VE</td>\n",
              "      <td>34.077906</td>\n",
              "      <td>70.697531</td>\n",
              "      <td>Afghanistan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1496</th>\n",
              "      <td>ID_M51GDSUBKS8Q</td>\n",
              "      <td>32.202177</td>\n",
              "      <td>48.344005</td>\n",
              "      <td>Iran</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1497</th>\n",
              "      <td>ID_469MTLRKJC64</td>\n",
              "      <td>32.340069</td>\n",
              "      <td>48.157425</td>\n",
              "      <td>Iran</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1498</th>\n",
              "      <td>ID_DMH9P3N6O3DK</td>\n",
              "      <td>14.260575</td>\n",
              "      <td>33.551627</td>\n",
              "      <td>Sudan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1499</th>\n",
              "      <td>ID_FKB2YZ2BXZ0Z</td>\n",
              "      <td>14.148376</td>\n",
              "      <td>33.371784</td>\n",
              "      <td>Sudan</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1500 rows × 4 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c17fd8f4-3a73-44c1-93be-53bfef525f2e')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-c17fd8f4-3a73-44c1-93be-53bfef525f2e button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-c17fd8f4-3a73-44c1-93be-53bfef525f2e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-2b3fbd6f-2145-4f63-804b-96cdb7374307\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-2b3fbd6f-2145-4f63-804b-96cdb7374307')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-2b3fbd6f-2145-4f63-804b-96cdb7374307 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ],
      "source": [
        "test_coords_df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L7dgHLP_kTQj",
        "outputId": "67ff16ec-ff56-4275-83aa-ee159e638d7e"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Afghanistan    500\n",
              "Iran           500\n",
              "Sudan          500\n",
              "Name: Country, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ],
      "source": [
        "# Checking if there are any Unknown Countries based on the given Coordinates\n",
        "train_country_counts = train_coords_df['Country'].value_counts()\n",
        "train_country_counts"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DZ3onCBqkUZW",
        "outputId": "09b99192-9429-42f1-ae98-1096bc14ab00"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Afghanistan    500\n",
              "Iran           500\n",
              "Sudan          500\n",
              "Name: Country, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ],
      "source": [
        "# Checking if there are any Unknown Countries based on the given Coordinates\n",
        "test_country_counts = test_coords_df['Country'].value_counts()\n",
        "test_country_counts"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "vsNEKiLdkYoq"
      },
      "outputs": [],
      "source": [
        "def get_country_data(df, country):\n",
        "    \"\"\"Create a separate DataFrame for each country\"\"\"\n",
        "    return df[df['Country'] == country]\n",
        "\n",
        "def create_dataframes(df_dict, countries):\n",
        "    \"\"\"Create train and test DataFrames for each country\"\"\"\n",
        "    country_dfs = {}\n",
        "    for key, df in df_dict.items():\n",
        "        country_dfs[key] = {country: get_country_data(df, country) for country in countries}\n",
        "    return country_dfs\n",
        "\n",
        "def print_country_dfs(country_dfs):\n",
        "    \"\"\"Print first 5 rows of the DataFrame for each country\"\"\"\n",
        "    for df_name, dfs in country_dfs.items():\n",
        "        for country, df in dfs.items():\n",
        "            print(f\"{country}_{df_name}_df: \\n\", df.head())\n",
        "\n",
        "## The buffer was added here to create a more homogenuous value.\n",
        "## After running several trials a value of 20 was found the best\n",
        "def create_featureCollection(row):\n",
        "    \"\"\"Create an Earth Engine FeatureCollection from the pandas DataFrame.\n",
        "      Each data point will have a buffer of 20 \"\"\"\n",
        "    point = ee.Feature(ee.Geometry.Point([row['Lon'], row['Lat']]))\n",
        "    buffered_point = point.buffer(20) # Add buffer to the point\n",
        "    return ee.Feature(buffered_point)\n",
        "\n",
        "\n",
        "def create_feature_collections(country_dfs):\n",
        "    \"\"\"Create FeatureCollections for each country from their respective DataFrames\"\"\"\n",
        "    country_fcs = {}\n",
        "    for df_name, dfs in country_dfs.items():\n",
        "        country_fcs[df_name] = {country: ee.FeatureCollection(\n",
        "            df.apply(lambda row: create_featureCollection(row), axis=1).tolist())\n",
        "            for country, df in dfs.items()}\n",
        "    return country_fcs\n",
        "\n",
        "\n",
        "\n",
        "countries = ['Afghanistan', 'Iran', 'Sudan']\n",
        "df_dict = {'train': train_coords_df, 'test': test_coords_df}\n",
        "\n",
        "# Create and print DataFrames for each country\n",
        "country_dfs = create_dataframes(df_dict, countries)\n",
        "print_country_dfs(country_dfs)\n",
        "\n",
        "# Create FeatureCollections for each country\n",
        "country_fcs = create_feature_collections(country_dfs)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xECKKLaZkdQJ"
      },
      "outputs": [],
      "source": [
        "def maskS2clouds(image):\n",
        "  \"\"\" Mask out clouds from the dataset using the quality mask provided with S2 data \"\"\"\n",
        "  qa = image.select('QA60');\n",
        "\n",
        "  # Bits 10 and 11 are clouds and cirrus, respectively.\n",
        "  cloudBitMask = 1 << 10\n",
        "  cirrusBitMask = 1 << 11\n",
        "\n",
        "  # Both flags should be set to zero, indicating clear conditions.\n",
        "  mask = qa.bitwiseAnd(cloudBitMask).eq(0) \\\n",
        "      .And(qa.bitwiseAnd(cirrusBitMask).eq(0))\n",
        "\n",
        "  return image.updateMask(mask).divide(10000)\n",
        "\n",
        "## Calculate vegetation indices: NDVI, NDRE, CC, NDWI, SAVI, EVI\n",
        "def addNDVI (image):\n",
        "    return image.addBands(image.expression('(NIR-RED)/(NIR+RED)',{\n",
        "      'NIR':image.select('B8'),\n",
        "      'RED':image.select('B4')\n",
        "    }).rename('NDVI'))\\\n",
        "      .copyProperties(image, [\"system:time_start\"])\n",
        "\n",
        "def addNDRE (image):\n",
        "    return image.addBands(image.expression('(NIR-RED_EDGE)/(NIR+RED_EDGE)',{\n",
        "      'NIR':image.select('B8'),\n",
        "      'RED_EDGE':image.select('B5')\n",
        "    }).rename('NDRE'))\\\n",
        "      .copyProperties(image, [\"system:time_start\"])\n",
        "\n",
        "\n",
        "def addCC (image):\n",
        "    return image.addBands(image.expression('(RED_EDGE3/RED_EDGE1)-1',{\n",
        "      'RED_EDGE3':image.select('B7'),\n",
        "      'RED_EDGE1':image.select('B5')\n",
        "    }).rename('CC'))\\\n",
        "      .copyProperties(image, [\"system:time_start\"])\n",
        "\n",
        "def addNDWI (image):\n",
        "    return image.addBands(image.expression('(GREEN - NIR)/(GREEN + NIR)',{\n",
        "      'NIR':image.select('B8'),\n",
        "      'GREEN':image.select('B3')\n",
        "    }).rename('NDWI'))\\\n",
        "      .copyProperties(image, [\"system:time_start\"])\n",
        "\n",
        "\n",
        "def addSAVI (image):\n",
        "    return image.addBands(image.expression('((NIR-RED)/(NIR+RED + 0.5)) * (1 + 0.5)',{\n",
        "      'NIR':image.select('B8'),\n",
        "      'RED':image.select('B4')\n",
        "    }).rename('SAVI'))\\\n",
        "      .copyProperties(image, [\"system:time_start\"])\n",
        "\n",
        "\n",
        "def addEVI (image):\n",
        "    return image.addBands(image.expression('2.5 * ((NIR-RED)/(NIR + 6 * RED - 7.5 * BLUE + 1))',{\n",
        "      'NIR':image.select('B8'),\n",
        "      'RED':image.select('B4'),\n",
        "      'BLUE':image.select('B2')\n",
        "    }).rename('EVI'))\\\n",
        "      .copyProperties(image, [\"system:time_start\"])\n",
        "\n",
        "\n",
        "## Retrieve S2 HARMONIZED time series dataset from GEE.\n",
        "## The dataset will be aggregated on a monthly basis.\n",
        "def get_S2_dataset(start_date, end_date):\n",
        "  bands = ['B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B8', 'B8A', 'B11', 'B12']\n",
        "  return ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED') \\\n",
        "            .filterDate(start_date, end_date) \\\n",
        "            .filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE', 5)) \\\n",
        "            .map(maskS2clouds) \\\n",
        "            .select(bands) \\\n",
        "            .map(addNDVI)\\\n",
        "            .map(addSAVI)\\\n",
        "            .map(addNDWI)\\\n",
        "            .map(addEVI)\\\n",
        "            .map(addNDRE)\\\n",
        "            .map(addCC) \\\n",
        "            .mean()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "2nSR2wmNlhyN"
      },
      "outputs": [],
      "source": [
        "def export_to_drive(country_fcs, datasets_metadata):\n",
        "    for mode in country_fcs.keys():\n",
        "        for country, fc_coords in country_fcs[mode].items():\n",
        "            for period, (start_date, end_date) in datasets_metadata[country].items():\n",
        "                # Get the dataset\n",
        "                dataset = get_S2_dataset(start_date, end_date)\n",
        "                # Reduce the regions\n",
        "                coord_var = dataset.reduceRegions(\n",
        "                    collection=fc_coords,\n",
        "                    reducer=ee.Reducer.mean(),\n",
        "                    scale=10,\n",
        "                )\n",
        "\n",
        "                task = ee.batch.Export.table.toDrive(\n",
        "                    collection=coord_var,\n",
        "                    description=f'S2_{mode}_{country}_coord_{period}',\n",
        "                    fileFormat='CSV',\n",
        "                    folder='GeoAI_cropland',\n",
        "                )\n",
        "                task.start()\n",
        "\n",
        "def merge_and_save_csv(country_fcs, datasets_metadata, country_dfs, features, data_csv_paths):\n",
        "    for mode in country_fcs.keys():\n",
        "        for country, fc_coords in country_fcs[mode].items():\n",
        "            for period, (start_date, end_date) in datasets_metadata[country].items():\n",
        "                data_csv = pd.read_csv(f'{data_csv_paths}/S2_{mode}_{country}_coord_{period}.csv')\n",
        "                merged_data = pd.concat([\n",
        "                    country_dfs[mode][country].reset_index(drop=True),\n",
        "                    data_csv[features].reset_index(drop=True)\n",
        "                ], axis=1)\n",
        "                merged_data.to_csv(f'S2_{mode}_data_{country}_{period}.csv', index=False)\n",
        "\n",
        "\n",
        "# Dictionaries for each country's dataset and train coordinates\n",
        "# Afghanistan: {Train/Test : April2022}\n",
        "# Sudan/Iran: {Train/Test : Jul2019-Jun2020}\n",
        "\n",
        "datasets_metadata = {\n",
        "    'Afghanistan': {'2022': ('2022-04-01', '2022-04-30')},\n",
        "\n",
        "    'Iran': {'07_2019': ('2019-07-01', '2019-07-31'),\n",
        "             '08_2019': ('2019-08-01', '2019-08-31'),\n",
        "             '09_2019': ('2019-09-01', '2019-09-30'),\n",
        "             '10_2019': ('2019-10-01', '2019-10-31'),\n",
        "             '11_2019': ('2019-11-01', '2019-11-30'),\n",
        "             '12_2019': ('2019-12-01', '2019-12-31'),\n",
        "             '01_2020': ('2020-01-01', '2020-01-31'),\n",
        "             '02_2020': ('2020-02-01', '2020-02-29'),\n",
        "             '03_2020': ('2020-03-01', '2020-03-31'),\n",
        "             '04_2020': ('2020-04-01', '2020-04-30'),\n",
        "             '05_2020': ('2020-05-01', '2020-05-31'),\n",
        "             '06_2020': ('2020-06-01', '2020-06-30')},\n",
        "\n",
        "    'Sudan': {'07_2019': ('2019-07-01', '2019-07-31'),\n",
        "             '08_2019': ('2019-08-01', '2019-08-31'),\n",
        "             '09_2019': ('2019-09-01', '2019-09-30'),\n",
        "             '10_2019': ('2019-10-01', '2019-10-31'),\n",
        "             '11_2019': ('2019-11-01', '2019-11-30'),\n",
        "             '12_2019': ('2019-12-01', '2019-12-31'),\n",
        "             '01_2020': ('2020-01-01', '2020-01-31'),\n",
        "             '02_2020': ('2020-02-01', '2020-02-29'),\n",
        "             '03_2020': ('2020-03-01', '2020-03-31'),\n",
        "             '04_2020': ('2020-04-01', '2020-04-30'),\n",
        "             '05_2020': ('2020-05-01', '2020-05-31'),\n",
        "             '06_2020': ('2020-06-01', '2020-06-30')}\n",
        "}\n",
        "\n",
        "features = ['B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B8', 'B8A', 'B11', 'B12', 'NDVI', 'NDWI', 'SAVI', 'EVI', 'NDRE', 'CC']\n",
        "data_csv_paths = '/content/drive/MyDrive/GeoAI_cropland'\n",
        "\n",
        "\n",
        "## This will export the dataset to your drive (you only need to run it once!)\n",
        "## !! This will take a bit of time so make sure you check that all the files got exported to the drive before running the next cells!!\n",
        "export_to_drive(country_fcs, datasets_metadata)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Z34wx7tPP4qV"
      },
      "outputs": [],
      "source": [
        "## This requires the dataset saved in the drive\n",
        "merge_and_save_csv(country_fcs, datasets_metadata, country_dfs, features, data_csv_paths)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NTRugIS1m0y9"
      },
      "source": [
        "##**Exploratory Data Analysis(EDA)**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "E6p9LxmbmymI"
      },
      "outputs": [],
      "source": [
        "dataframes = {}\n",
        "modes = ['train', 'test']\n",
        "for mode in modes:\n",
        "  dataframes[mode] = {}\n",
        "  for country in datasets_metadata.keys():\n",
        "    for period in datasets_metadata[country].keys():\n",
        "      file_name = f'/content/S2_{mode}_data_{country}_{period}.csv'\n",
        "      dataframes[mode][f'{country}_{period}'] = pd.read_csv(file_name)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# List of months\n",
        "months = ['07_2019', '08_2019', '09_2019', '10_2019', '11_2019', '12_2019', '01_2020', '02_2020', '03_2020', '04_2020', '05_2020', '06_2020']\n",
        "\n",
        "# Function to concatenate and rename columns for a specific DataFrame\n",
        "def concatenate_and_rename(dataframes, country_name, df_name, months, exclude_columns):\n",
        "    # Initialize an empty list to store DataFrames\n",
        "    dataframes_list = []\n",
        "\n",
        "    # Loop through the months and concatenate DataFrames with column renaming\n",
        "    for month in months:\n",
        "        df = dataframes[df_name][f'{country_name}_{month}']\n",
        "        df = df.drop('Country', axis=1)\n",
        "        df = df.rename(columns={col: col + f'_{month}' for col in df.columns if col not in exclude_columns})\n",
        "        dataframes_list.append(df)\n",
        "\n",
        "    # Use reduce to concatenate the DataFrames\n",
        "    result = reduce(lambda left, right: pd.merge(left, right, on=exclude_columns, how='inner'), dataframes_list)\n",
        "\n",
        "    return result\n",
        "\n",
        "\n",
        "# List of columns to exclude from suffixing (timeless columns)\n",
        "exclude_columns = ['Lon', 'Lat', 'ID', 'Target']\n",
        "\n",
        "# Concatenate and rename columns for the train DataFrame\n",
        "Afghanistan_train_data = dataframes['train']['Afghanistan_2022']\n",
        "Iran_train_data = concatenate_and_rename(dataframes, 'Iran', 'train', months, exclude_columns)\n",
        "Sudan_train_data = concatenate_and_rename(dataframes, 'Sudan', 'train', months, exclude_columns)\n",
        "\n",
        "# Concatenate and rename columns for the test DataFrame\n",
        "Afghanistan_test_data = dataframes['test']['Afghanistan_2022']\n",
        "Iran_test_data = concatenate_and_rename(dataframes, 'Iran', 'test', months, exclude_columns[:3])\n",
        "Sudan_test_data = concatenate_and_rename(dataframes, 'Sudan', 'test', months, exclude_columns[:3])"
      ],
      "metadata": {
        "id": "w8vmoX2XjFdp"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Feature Selection**"
      ],
      "metadata": {
        "id": "MVipYggqViEU"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "For feature selection, I used Boruta algorithm.\n",
        "\n",
        "Boruta is typically used in machine learning and data analysis when there is a large number of features and you want to determine which ones are most relevant to the target variable. It helps improve model performance and reduce overfitting.\n",
        "\n",
        "Boruta uses a random forest classifier (or regressor, depending on the problem) to assess feature importance. It works by comparing the importance of the actual features with the importance of random \"shadow\" features.\n",
        "\n",
        "Process:\n",
        "\n",
        "The starting point is the original dataset, which includes features and the target variable.\n",
        "Boruta creates a set of random shadow features that have no actual relationship with the target variable. These shadow features represent the null hypothesis that a feature is not important.\n",
        "Boruta combines the real features with the shadow features and trains a random forest model.\n",
        "The feature importance scores for the real features are compared to the importance scores of the shadow features. Features that have significantly higher importance scores than the shadow features are considered relevant.\n",
        "Boruta selects the features that are deemed important based on the comparison with the shadow features. These selected features are considered valuable for predicting the target variable."
      ],
      "metadata": {
        "id": "fdeewOrKcAau"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def get_important_features(X, y):\n",
        "  # Initiliaze Random Forest CLassifier\n",
        "  rf = RandomForestClassifier(max_depth=20)\n",
        "  # Fit Random Forest on provided data\n",
        "  rf.fit(X,y)\n",
        "  # Create dictionary of feature importances\n",
        "  importances = {feature_name: f_importance for feature_name, f_importance in zip(X.columns, rf.feature_importances_)}\n",
        "  # Isolate importances of Shadow features\n",
        "  only_shadow_feat_importance = {key:value for key,value in importances.items() if \"shadow\" in key}\n",
        "  # get importance level of most important shadow feature\n",
        "  highest_shadow_feature = list(dict(sorted(only_shadow_feat_importance.items(), key=lambda item: item[1], reverse=True)).values())[0]\n",
        "  # get original feature which fulfill boruta selection criteria\n",
        "  selected_features = [key for key, value in importances.items() if value > highest_shadow_feature]\n",
        "  return selected_features"
      ],
      "metadata": {
        "id": "RxnXME5LVkqc"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dataframes = [Afghanistan_train_data, Sudan_train_data, Iran_train_data]\n",
        "\n",
        "for df in dataframes:\n",
        "    for col in df.columns:\n",
        "        df[f\"shadow_{col}\"] = df[col].sample(frac=1).reset_index(drop=True)"
      ],
      "metadata": {
        "id": "iHg5n5i4isDu"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Calculate the probability mass function\n",
        "TRIALS = 50\n",
        "pmf = [sp.stats.binom.pmf(x, TRIALS, .5) for x in range(TRIALS + 1)]\n",
        "def get_tail_items(pmf):\n",
        "  total = 0\n",
        "  for i, x in enumerate(pmf):\n",
        "    total += x\n",
        "    if total >= 0.05:\n",
        "        break\n",
        "  return i\n",
        "\n",
        "# plot the binomial distribution\n",
        "plt.plot([i for i in range(TRIALS + 1)], pmf,\"-o\")\n",
        "plt.title(f\"Binomial distribution for {TRIALS} trials\")\n",
        "plt.xlabel(\"No. of trials\")\n",
        "plt.ylabel(\"Probability\")\n",
        "plt.grid(True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 524
        },
        "id": "uepI1XHTCqSA",
        "outputId": "755e7591-0ee4-4d03-bc5d-a385ba1e8b84"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x550 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# select features from n number of trials\n",
        "def choose_features(feature_hits, TRIALS, thresh):\n",
        "    #define boundries\n",
        "    green_zone_thresh = TRIALS - thresh\n",
        "    blue_zone_upper = green_zone_thresh\n",
        "    blue_zone_lower = thresh\n",
        "    green_zone = [key for key, value in feature_hits.items() if    value >= green_zone_thresh]\n",
        "    blue_zone = [key for key, value in feature_hits.items() if (value >= blue_zone_lower and value < blue_zone_upper)]\n",
        "    return green_zone, blue_zone"
      ],
      "metadata": {
        "id": "FhuP8hQ9DPjB"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Afghanistan\n",
        "afgh_train_X = Afghanistan_train_data.drop(['ID', 'shadow_ID', 'shadow_Country',  'Target', 'Country'], axis = 1).fillna(0)\n",
        "afgn_train_Y = Afghanistan_train_data.Target\n",
        "\n",
        "#Iran\n",
        "Iran_train_X = Iran_train_data.drop(['ID', 'shadow_ID', 'Target'], axis = 1).fillna(0)\n",
        "Iran_train_Y = Iran_train_data.Target\n",
        "\n",
        "#Sudan\n",
        "Sudan_train_X = Sudan_train_data.drop(['ID', 'shadow_ID', 'Target'], axis = 1).fillna(0)\n",
        "Sudan_train_Y = Sudan_train_data.Target"
      ],
      "metadata": {
        "id": "qc6e5GscV6nP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def compute_feature_hits(country_data, country_train_X, country_train_Y, TRIALS=50):\n",
        "    feature_hits = {i: 0 for i in country_data.drop(['ID'], axis=1).fillna(0).columns}\n",
        "\n",
        "    for _ in tqdm(range(TRIALS)):\n",
        "        imp_features = get_important_features(country_train_X, country_train_Y)\n",
        "        for key in feature_hits:\n",
        "            if key in imp_features:\n",
        "                feature_hits[key] += 1\n",
        "\n",
        "    return feature_hits\n",
        "\n",
        "\n",
        "thresh = get_tail_items(pmf)\n",
        "countries = {\n",
        "    'Afghanistan': (Afghanistan_train_data, afgh_train_X, afgn_train_Y),\n",
        "    'Iran': (Iran_train_data, Iran_train_X, Iran_train_Y),\n",
        "    'Sudan': (Sudan_train_data, Sudan_train_X, Sudan_train_Y)\n",
        "}\n",
        "\n",
        "results = {}\n",
        "relevant_features = {}\n",
        "for country, (country_data, country_train_X, country_train_Y) in countries.items():\n",
        "    feature_hits = compute_feature_hits(country_data, country_train_X, country_train_Y)\n",
        "    results[country] = feature_hits\n",
        "    green, blue = choose_features(feature_hits, TRIALS, thresh)\n",
        "    print(len(green), len(blue))\n",
        "    relevant_features[country] = green + blue\n",
        "    print(f'{country} Most Relevant Features: {feature_hits}')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237,
          "referenced_widgets": [
            "2cdfe2997a3043ce85b6e460a0c3f1d6",
            "a0b1f9d0c8df4e29a907318a4b4bc433",
            "7c0b2b89936e418e9d66383ecab14964",
            "cc3d1fc3a8ef4c1a82bd6ae0a72d8f1f",
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            "437daebe84e74335971c7e3c22c21e08",
            "c0a81c8251c345f08cbca10ae97ec001",
            "e6780b44d5d142acb1e0e8412c690e79",
            "54c520978c9644e18173b42417313fe2",
            "2a1c575f9e80443ea07f76a45579fc2e",
            "15b4bd70c4be476888736807b833460f",
            "1e2dcde97b6740e59c2172927fad15d3",
            "24e8b4acfc7546a4a84a1f9afe0620f0",
            "78fbdd9b7cfe4551a8996c6b8a1ad227",
            "0fad82a04fc64b38a7c25a42afb89002",
            "9b179f15628349a380284974ce71d478",
            "f0cac26528d74038ac44db999f9ab7e3",
            "865d0d7bb2804cf887d71888ec24180d",
            "4789cae81d8c427bb9dc3acf476b3e06",
            "12ab3b958fb640f9a1ec6f891df813eb",
            "6bf04405c5144918860dea7fc61a241d",
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            "160e2d6967924cab8c61ca95eb77f496",
            "ffeaab3683fe4d2a9a64aa893f1119d1",
            "83f34fa5e4754d309239426a61fcbbd6",
            "92dc151715fd4ce593c12d45f8d581a0",
            "3bd81cef40f843a881a772358dd3d89d",
            "c32bea9bf3c3448faca59831ea9fc2f4",
            "4e12379b90574bedaf0a134e7f93fa78",
            "28f8db44a5bd4430ac0a1b157734c74d",
            "d26642eea02d4db695e8a917efd013a7",
            "d7bdb251c63344fca0d6295429f8326a",
            "ec0af57308a04cc692e820c2349c1286"
          ]
        },
        "id": "tPsA2QYYlPpJ",
        "outputId": "13296969-7641-4d48-ef4e-04b367aa0b54"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/50 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "2cdfe2997a3043ce85b6e460a0c3f1d6"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "15 2\n",
            "Afghanistan Most Relevant Features: {'Lat': 50, 'Lon': 50, 'Target': 0, 'Country': 0, 'B2': 50, 'B3': 34, 'B4': 47, 'B5': 26, 'B6': 1, 'B7': 19, 'B8': 33, 'B8A': 32, 'B11': 39, 'B12': 50, 'NDVI': 50, 'NDWI': 50, 'SAVI': 50, 'EVI': 50, 'NDRE': 50, 'CC': 50, 'shadow_ID': 0, 'shadow_Lat': 0, 'shadow_Lon': 0, 'shadow_Target': 0, 'shadow_Country': 0, 'shadow_B2': 0, 'shadow_B3': 0, 'shadow_B4': 0, 'shadow_B5': 0, 'shadow_B6': 0, 'shadow_B7': 0, 'shadow_B8': 0, 'shadow_B8A': 0, 'shadow_B11': 0, 'shadow_B12': 0, 'shadow_NDVI': 0, 'shadow_NDWI': 0, 'shadow_SAVI': 0, 'shadow_EVI': 0, 'shadow_NDRE': 0, 'shadow_CC': 0}\n"
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            "84 20\n",
            "Iran Most Relevant Features: {'Lat': 14, 'Lon': 39, 'Target': 0, 'B2_07_2019': 6, 'B3_07_2019': 2, 'B4_07_2019': 3, 'B5_07_2019': 6, 'B6_07_2019': 2, 'B7_07_2019': 0, 'B8_07_2019': 4, 'B8A_07_2019': 2, 'B11_07_2019': 2, 'B12_07_2019': 1, 'NDVI_07_2019': 26, 'NDWI_07_2019': 30, 'SAVI_07_2019': 37, 'EVI_07_2019': 40, 'NDRE_07_2019': 9, 'CC_07_2019': 17, 'B2_08_2019': 16, 'B3_08_2019': 10, 'B4_08_2019': 6, 'B5_08_2019': 9, 'B6_08_2019': 2, 'B7_08_2019': 0, 'B8_08_2019': 1, 'B8A_08_2019': 7, 'B11_08_2019': 13, 'B12_08_2019': 1, 'NDVI_08_2019': 3, 'NDWI_08_2019': 3, 'SAVI_08_2019': 0, 'EVI_08_2019': 2, 'NDRE_08_2019': 0, 'CC_08_2019': 2, 'B2_09_2019': 21, 'B3_09_2019': 19, 'B4_09_2019': 26, 'B5_09_2019': 29, 'B6_09_2019': 0, 'B7_09_2019': 0, 'B8_09_2019': 0, 'B8A_09_2019': 1, 'B11_09_2019': 35, 'B12_09_2019': 6, 'NDVI_09_2019': 31, 'NDWI_09_2019': 32, 'SAVI_09_2019': 40, 'EVI_09_2019': 36, 'NDRE_09_2019': 31, 'CC_09_2019': 40, 'B2_10_2019': 50, 'B3_10_2019': 38, 'B4_10_2019': 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            "132 31\n",
            "Sudan Most Relevant Features: {'Lat': 48, 'Lon': 14, 'Target': 0, 'B2_07_2019': 23, 'B3_07_2019': 40, 'B4_07_2019': 44, 'B5_07_2019': 46, 'B6_07_2019': 50, 'B7_07_2019': 50, 'B8_07_2019': 50, 'B8A_07_2019': 49, 'B11_07_2019': 50, 'B12_07_2019': 49, 'NDVI_07_2019': 44, 'NDWI_07_2019': 44, 'SAVI_07_2019': 49, 'EVI_07_2019': 50, 'NDRE_07_2019': 38, 'CC_07_2019': 38, 'B2_08_2019': 0, 'B3_08_2019': 0, 'B4_08_2019': 0, 'B5_08_2019': 0, 'B6_08_2019': 0, 'B7_08_2019': 0, 'B8_08_2019': 0, 'B8A_08_2019': 0, 'B11_08_2019': 0, 'B12_08_2019': 0, 'NDVI_08_2019': 0, 'NDWI_08_2019': 0, 'SAVI_08_2019': 0, 'EVI_08_2019': 0, 'NDRE_08_2019': 0, 'CC_08_2019': 0, 'B2_09_2019': 36, 'B3_09_2019': 40, 'B4_09_2019': 36, 'B5_09_2019': 46, 'B6_09_2019': 29, 'B7_09_2019': 39, 'B8_09_2019': 42, 'B8A_09_2019': 45, 'B11_09_2019': 4, 'B12_09_2019': 26, 'NDVI_09_2019': 38, 'NDWI_09_2019': 24, 'SAVI_09_2019': 47, 'EVI_09_2019': 49, 'NDRE_09_2019': 47, 'CC_09_2019': 50, 'B2_10_2019': 47, 'B3_10_2019': 48, 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'shadow_NDVI_05_2020': 0, 'shadow_NDWI_05_2020': 0, 'shadow_SAVI_05_2020': 0, 'shadow_EVI_05_2020': 0, 'shadow_NDRE_05_2020': 0, 'shadow_CC_05_2020': 0, 'shadow_B2_06_2020': 0, 'shadow_B3_06_2020': 0, 'shadow_B4_06_2020': 0, 'shadow_B5_06_2020': 0, 'shadow_B6_06_2020': 0, 'shadow_B7_06_2020': 0, 'shadow_B8_06_2020': 0, 'shadow_B8A_06_2020': 0, 'shadow_B11_06_2020': 0, 'shadow_B12_06_2020': 0, 'shadow_NDVI_06_2020': 0, 'shadow_NDWI_06_2020': 0, 'shadow_SAVI_06_2020': 0, 'shadow_EVI_06_2020': 0, 'shadow_NDRE_06_2020': 0, 'shadow_CC_06_2020': 0}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UmgNAaJuowqf"
      },
      "source": [
        "## **Model Evaluation**"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "In this section, I checked how well the baseline classifers (RF, KNN, LDA, LR, QDA, CART, BAG, Ada, GBC, Lgbm, XGB) can learn from this dataset using 5 fold cross validation. This will help identify  the top-performing models and pinpointing those that may benefit from further refinement. This is done for each country separetly.\n"
      ],
      "metadata": {
        "id": "u-GPoK47c_Tg"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Kfeznl2BoosS"
      },
      "outputs": [],
      "source": [
        "def evaluate_models(train_data, models):\n",
        "    \"\"\"\n",
        "    evaluate each model in turn (spot checking algorithms (of baselines))\n",
        "    \"\"\"\n",
        "\n",
        "    print(\"{:<10} | {:<15} | {:<15}\".format('Model', 'Accuracy (mean)', 'Accuracy (std)'))\n",
        "    print(\"--------------------------------------------\")\n",
        "\n",
        "    train_X = train_data.drop(['ID', 'Target'], axis = 1).fillna(0)\n",
        "    train_Y = train_data.Target\n",
        "    acc, names = [], []\n",
        "\n",
        "    for name, model in models:\n",
        "      names.append(name)\n",
        "      cv_results = cross_val_score(\n",
        "          model,\n",
        "          train_X,\n",
        "          train_Y,\n",
        "          cv=5,\n",
        "          scoring='accuracy',\n",
        "          n_jobs=-1,\n",
        "          error_score='raise'\n",
        "          )\n",
        "\n",
        "      acc.append(cv_results)\n",
        "      print(\"{:<10} | {:<15.3f} | {:<15.3f}\".format(name, cv_results.mean(), cv_results.std()))\n",
        "      print(\"--------------------------------------------\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ho-3cHtjq1mM"
      },
      "outputs": [],
      "source": [
        "# Model selection\n",
        "# Create a list of standard classifiers\n",
        "models = []\n",
        "models.append(('LDA', LinearDiscriminantAnalysis()))\n",
        "models.append(('QDA', QuadraticDiscriminantAnalysis()))\n",
        "models.append(('LR', LogisticRegression(random_state=SEED, n_jobs=-1)))\n",
        "models.append(('CART', DecisionTreeClassifier(random_state=SEED)))\n",
        "models.append(('KNN', KNeighborsClassifier(n_jobs=-1)))\n",
        "models.append(('Bag', BaggingClassifier(random_state=SEED, n_jobs=-1)))\n",
        "models.append(('Ada', AdaBoostClassifier(random_state=SEED)))\n",
        "models.append(('RF', RandomForestClassifier(n_jobs=-1,random_state=SEED)))\n",
        "models.append(('GBC', GradientBoostingClassifier(random_state=SEED)))\n",
        "models.append(('Lgbm', LGBMClassifier(random_state=SEED, objective='binary', metric='binary_logloss')))\n",
        "models.append(('XGB', XGBClassifier(n_jobs=-1, random_state=SEED, objective='binary:logistic', eval_metric='logloss')))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_r0-b-uWq28r"
      },
      "source": [
        "**Compare baseline models**"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "stable_cols_Afgh = ['ID','Target']\n",
        "stable_cols_Sudan = ['ID','Lon', 'Target',]\n",
        "stable_cols_Iran = ['ID', 'Lat', 'Target']"
      ],
      "metadata": {
        "id": "e6C-w6hLzOz_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Afghanistan_train_data = Afghanistan_train_data[relevant_features['Afghanistan'] + stable_cols_Afgh]\n",
        "Iran_train_data = Iran_train_data[relevant_features['Iran'] + stable_cols_Iran]\n",
        "Sudan_train_data = Sudan_train_data[relevant_features['Sudan'] + stable_cols_Sudan]"
      ],
      "metadata": {
        "id": "EdwdFKLYGoWo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#evaluate the models using the Afghanistan train data\n",
        "evaluate_models(Afghanistan_train_data, models)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uon96Y5N82fB",
        "outputId": "87fcb8c6-fbd6-4005-d508-632cc7135c6b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model      | Accuracy (mean) | Accuracy (std) \n",
            "--------------------------------------------\n",
            "LDA        | 0.810           | 0.021          \n",
            "--------------------------------------------\n",
            "QDA        | 0.804           | 0.048          \n",
            "--------------------------------------------\n",
            "LR         | 0.762           | 0.031          \n",
            "--------------------------------------------\n",
            "CART       | 0.762           | 0.012          \n",
            "--------------------------------------------\n",
            "KNN        | 0.800           | 0.018          \n",
            "--------------------------------------------\n",
            "Bag        | 0.808           | 0.026          \n",
            "--------------------------------------------\n",
            "Ada        | 0.798           | 0.032          \n",
            "--------------------------------------------\n",
            "RF         | 0.810           | 0.023          \n",
            "--------------------------------------------\n",
            "GBC        | 0.842           | 0.023          \n",
            "--------------------------------------------\n",
            "Lgbm       | 0.834           | 0.029          \n",
            "--------------------------------------------\n",
            "XGB        | 0.840           | 0.029          \n",
            "--------------------------------------------\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#evaluate the models using the Sudan train data\n",
        "evaluate_models(Sudan_train_data, models)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fPn15Z4V89Zg",
        "outputId": "d3a81d34-f446-47f1-8796-9c9bd81ae250"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model      | Accuracy (mean) | Accuracy (std) \n",
            "--------------------------------------------\n",
            "LDA        | 0.970           | 0.014          \n",
            "--------------------------------------------\n",
            "QDA        | 0.976           | 0.005          \n",
            "--------------------------------------------\n",
            "LR         | 0.942           | 0.013          \n",
            "--------------------------------------------\n",
            "CART       | 0.938           | 0.022          \n",
            "--------------------------------------------\n",
            "KNN        | 0.980           | 0.011          \n",
            "--------------------------------------------\n",
            "Bag        | 0.972           | 0.016          \n",
            "--------------------------------------------\n",
            "Ada        | 0.968           | 0.013          \n",
            "--------------------------------------------\n",
            "RF         | 0.978           | 0.010          \n",
            "--------------------------------------------\n",
            "GBC        | 0.972           | 0.012          \n",
            "--------------------------------------------\n",
            "Lgbm       | 0.976           | 0.010          \n",
            "--------------------------------------------\n",
            "XGB        | 0.976           | 0.012          \n",
            "--------------------------------------------\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#evaluate the models using the Iran train data\n",
        "evaluate_models(Iran_train_data, models)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JuVoZ88r2BRO",
        "outputId": "b7b6c916-4c46-4d90-a4c6-9c1320c35fdb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model      | Accuracy (mean) | Accuracy (std) \n",
            "--------------------------------------------\n",
            "LDA        | 0.936           | 0.019          \n",
            "--------------------------------------------\n",
            "QDA        | 0.944           | 0.022          \n",
            "--------------------------------------------\n",
            "LR         | 0.934           | 0.033          \n",
            "--------------------------------------------\n",
            "CART       | 0.902           | 0.034          \n",
            "--------------------------------------------\n",
            "KNN        | 0.944           | 0.028          \n",
            "--------------------------------------------\n",
            "Bag        | 0.932           | 0.033          \n",
            "--------------------------------------------\n",
            "Ada        | 0.938           | 0.032          \n",
            "--------------------------------------------\n",
            "RF         | 0.956           | 0.024          \n",
            "--------------------------------------------\n",
            "GBC        | 0.940           | 0.028          \n",
            "--------------------------------------------\n",
            "Lgbm       | 0.954           | 0.027          \n",
            "--------------------------------------------\n",
            "XGB        | 0.954           | 0.022          \n",
            "--------------------------------------------\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6JzuCd_6rlKp"
      },
      "source": [
        "**Hyperparameter Tuning**"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Based on the preceding results, it is evident that XGBoost consistently outperforms the other models across all three countries.\n",
        "\n",
        "In this section, I will focus on tuning XGBoost hyperparameters exclusively using the training data and cross-validation techniques for each country separetly.\n",
        "\n",
        "Hyperparameter tuning is done here uing Optuna. Optuna offers a more sophisticated approach to hyperparameter tuning compared to traditional methods like grid search or random search. Grid search systematically tries every possible combination of parameters, which can be computationally expensive and time-consuming, especially when the hyperparameter space is vast. Random search, on the other hand, selects random combinations of parameters but offers no guarantee of finding the optimal set within a given number of trials. Optuna, however, employs a Bayesian optimization-based strategy, which uses the information from previous trials to suggest more promising parameter combinations. This \"intelligent\" sampling leads to more efficient searches, often requiring fewer trials to find optimal or near-optimal hyperparameters."
      ],
      "metadata": {
        "id": "onKAAMP_fcQg"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "yfd6ibRWth-V"
      },
      "outputs": [],
      "source": [
        "def create_knn(trial):\n",
        "    return KNeighborsClassifier(\n",
        "        n_neighbors=trial.suggest_int(\"n_neighbors\", 2, 50),\n",
        "        n_jobs=-1)\n",
        "\n",
        "\n",
        "def create_qda(trial):\n",
        "    return QuadraticDiscriminantAnalysis(\n",
        "        reg_param=trial.suggest_float(\"reg_param\", 0.0, 1.0)\n",
        "        )\n",
        "\n",
        "\n",
        "\n",
        "def create_bag(trial):\n",
        "    return BaggingClassifier(\n",
        "        n_estimators=trial.suggest_int(\"n_estimators\", 50, 2000),\n",
        "        random_state=SEED,\n",
        "        n_jobs=-1\n",
        "        )\n",
        "\n",
        "\n",
        "def create_gbc(trial):\n",
        "    return GradientBoostingClassifier(\n",
        "        n_estimators=trial.suggest_int(\"n_estimators\", 50, 2000),\n",
        "        max_depth=trial.suggest_int(\"max_depth\", 5, 40, log=True),\n",
        "        learning_rate=trial.suggest_float(\"learning_rate\", 1e-4, 1e-1, log=True),\n",
        "        random_state=SEED\n",
        "        )\n",
        "\n",
        "def create_rf(trial):\n",
        "    return RandomForestClassifier(\n",
        "        n_estimators=trial.suggest_int(\"n_estimators\", 50, 3000),\n",
        "        max_depth=trial.suggest_int(\"max_depth\", 5, 40, log=True),\n",
        "        criterion=trial.suggest_categorical(\"criterion\", [\"gini\", \"entropy\"]),\n",
        "        min_samples_split=trial.suggest_float(\"min_samples_split\", 0.1, 1.0),\n",
        "        min_samples_leaf=trial.suggest_float(\"min_samples_leaf\", 0.1, 0.5),\n",
        "        max_features=trial.suggest_categorical(\"max_features\", [\"auto\", \"sqrt\", \"log2\"]),\n",
        "        random_state=SEED\n",
        "    )\n",
        "\n",
        "def create_lgbm(trial):\n",
        "    return LGBMClassifier(\n",
        "        learning_rate=trial.suggest_float(\"learning_rate\", 1e-4, 1e-1, log=True),\n",
        "        n_estimators=trial.suggest_int(\"n_estimators\", 50, 2000),\n",
        "        boosting_type=trial.suggest_categorical(\"boosting_type\", [\"gbdt\", \"dart\"]),\n",
        "        max_depth=trial.suggest_int(\"max_depth\", 5, 40, log=True),\n",
        "        num_leaves=trial.suggest_int(\"num_leaves\", 2, 500),\n",
        "        min_child_samples=trial.suggest_int(\"min_child_samples\", 10, 300),\n",
        "        feature_fraction=trial.suggest_float(\"feature_fraction\", 0.1, 1.0),\n",
        "        bagging_fraction=trial.suggest_float(\"bagging_fraction\", 0.1, 1.0),\n",
        "        bagging_freq=trial.suggest_int(\"bagging_freq\", 1, 7),\n",
        "        objective='binary',\n",
        "        metric='binary_logloss',\n",
        "        random_state=SEED\n",
        "    )\n",
        "\n",
        "def create_xgb(trial):\n",
        "    return XGBClassifier(\n",
        "        learning_rate=trial.suggest_float(\"learning_rate\", 1e-5, 1e-1, log=True),\n",
        "        n_estimators=trial.suggest_int(\"n_estimators\", 50, 3000),\n",
        "        max_depth=trial.suggest_int(\"max_depth\", 5, 50, log=True),\n",
        "        subsample=trial.suggest_float(\"subsample\", 0.1, 1.0),\n",
        "        colsample_bytree=trial.suggest_float(\"colsample_bytree\", 0.1, 1.0),\n",
        "        n_jobs=-1,\n",
        "        objective='binary:logistic',\n",
        "        eval_metric='logloss',\n",
        "        random_state=SEED\n",
        "    )\n",
        "\n",
        "\n",
        "\n",
        "def objective(train_data, model_type, trial):\n",
        "    model = MODEL_FUNCS[model_type](trial)\n",
        "\n",
        "    train_X = train_data.drop(['ID', 'Target'], axis = 1).fillna(0)\n",
        "    train_Y = train_data.Target\n",
        "\n",
        "    # Use cross_val_predict to get predicted probabilities for each fold\n",
        "    cv_results = cross_val_score(\n",
        "        model,\n",
        "        train_X,\n",
        "        train_Y,\n",
        "        cv=5,\n",
        "        scoring='accuracy',\n",
        "        n_jobs=-1,\n",
        "        error_score='raise'\n",
        "          )\n",
        "\n",
        "    return cv_results.mean()\n",
        "\n",
        "\n",
        "# Optuna Optimization\n",
        "MODEL_FUNCS = {\n",
        "    'gbc': create_gbc,\n",
        "    'bag': create_bag,\n",
        "    'knn': create_knn,\n",
        "    'qda': create_qda,\n",
        "    'rf': create_rf,\n",
        "    'lgbm': create_lgbm,\n",
        "    'xgb': create_xgb\n",
        "}\n",
        "\n",
        "\n",
        "# Objective Function for Optuna\n",
        "def run_optimization(model_type, train_data, n_trials=100):\n",
        "    study = optuna.create_study(direction=\"maximize\")\n",
        "    study.optimize(lambda trial: objective(train_data, model_type, trial), n_trials=n_trials)\n",
        "    print(f\"{model_type.upper()} best parameters: \", study.best_params)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GxuUjQbhbrmC",
        "outputId": "ccf47988-a531-4480-e18d-b272cab582f9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[I 2023-09-21 14:10:37,945] A new study created in memory with name: no-name-5aa03491-c853-497d-858a-3798be2993a9\n",
            "[I 2023-09-21 14:10:39,294] Trial 0 finished with value: 0.79 and parameters: {'learning_rate': 1.879666980054014e-05, 'n_estimators': 456, 'max_depth': 40, 'subsample': 0.41926320060567424, 'colsample_bytree': 0.4662464220803345}. Best is trial 0 with value: 0.79.\n",
            "[I 2023-09-21 14:10:42,916] Trial 1 finished with value: 0.8300000000000001 and parameters: {'learning_rate': 0.028393325376357102, 'n_estimators': 730, 'max_depth': 11, 'subsample': 0.7376572722585373, 'colsample_bytree': 0.7620098814045577}. Best is trial 1 with value: 0.8300000000000001.\n",
            "[I 2023-09-21 14:10:49,766] Trial 2 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.012999348057472127, 'n_estimators': 1238, 'max_depth': 8, 'subsample': 0.4425803628749465, 'colsample_bytree': 0.7223469448795189}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:10:59,568] Trial 3 finished with value: 0.8039999999999999 and parameters: {'learning_rate': 1.6600303559341865e-05, 'n_estimators': 1467, 'max_depth': 48, 'subsample': 0.9289034484535168, 'colsample_bytree': 0.8420846048945168}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:11:10,906] Trial 4 finished with value: 0.826 and parameters: {'learning_rate': 0.013429914641129994, 'n_estimators': 2129, 'max_depth': 16, 'subsample': 0.8304630939116227, 'colsample_bytree': 0.7637626727140602}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:11:16,510] Trial 5 finished with value: 0.8219999999999998 and parameters: {'learning_rate': 0.003732605441366316, 'n_estimators': 2041, 'max_depth': 34, 'subsample': 0.20350844381934824, 'colsample_bytree': 0.921206253964326}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:11:23,264] Trial 6 finished with value: 0.8239999999999998 and parameters: {'learning_rate': 0.06463594966534446, 'n_estimators': 2075, 'max_depth': 7, 'subsample': 0.5553067283052728, 'colsample_bytree': 0.6400368570441106}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:11:29,325] Trial 7 finished with value: 0.8019999999999999 and parameters: {'learning_rate': 0.00046607362603578225, 'n_estimators': 2615, 'max_depth': 40, 'subsample': 0.27214972208446453, 'colsample_bytree': 0.5106322044764765}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:11:32,979] Trial 8 finished with value: 0.834 and parameters: {'learning_rate': 0.04882828236101529, 'n_estimators': 855, 'max_depth': 47, 'subsample': 0.9831072669837109, 'colsample_bytree': 0.5260187239698235}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:11:37,689] Trial 9 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.0018537632695045012, 'n_estimators': 686, 'max_depth': 25, 'subsample': 0.39454909223159484, 'colsample_bytree': 0.7647923426598465}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:11:39,615] Trial 10 finished with value: 0.8 and parameters: {'learning_rate': 0.007822856390835532, 'n_estimators': 1366, 'max_depth': 5, 'subsample': 0.13298135065585132, 'colsample_bytree': 0.21471873654914575}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:11:42,524] Trial 11 finished with value: 0.82 and parameters: {'learning_rate': 0.07833212756297037, 'n_estimators': 993, 'max_depth': 18, 'subsample': 0.9794389409628805, 'colsample_bytree': 0.5605806177962158}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:11:43,285] Trial 12 finished with value: 0.8319999999999999 and parameters: {'learning_rate': 0.09195433451909318, 'n_estimators': 115, 'max_depth': 11, 'subsample': 0.6757399283871739, 'colsample_bytree': 0.9683419943910214}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:11:46,652] Trial 13 finished with value: 0.828 and parameters: {'learning_rate': 0.01544291914915608, 'n_estimators': 1121, 'max_depth': 24, 'subsample': 0.6416747470201595, 'colsample_bytree': 0.37947671514314074}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:11:55,616] Trial 14 finished with value: 0.8300000000000001 and parameters: {'learning_rate': 0.024146080360292522, 'n_estimators': 1764, 'max_depth': 11, 'subsample': 0.8166059148245357, 'colsample_bytree': 0.6438604080808722}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:11:56,004] Trial 15 finished with value: 0.806 and parameters: {'learning_rate': 0.005570361158573681, 'n_estimators': 103, 'max_depth': 50, 'subsample': 0.5063720775963539, 'colsample_bytree': 0.36152082571825317}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:12:00,503] Trial 16 finished with value: 0.8160000000000001 and parameters: {'learning_rate': 0.0008782506837790832, 'n_estimators': 1091, 'max_depth': 27, 'subsample': 0.5790454675130339, 'colsample_bytree': 0.6404665316990152}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:12:07,966] Trial 17 finished with value: 0.826 and parameters: {'learning_rate': 0.029553780836352753, 'n_estimators': 2948, 'max_depth': 18, 'subsample': 0.9817260777275445, 'colsample_bytree': 0.19843476410321026}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:12:12,949] Trial 18 finished with value: 0.8160000000000001 and parameters: {'learning_rate': 0.0037082733120757444, 'n_estimators': 507, 'max_depth': 8, 'subsample': 0.8497834640804867, 'colsample_bytree': 0.9970169174961163}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:12:18,206] Trial 19 finished with value: 0.8299999999999998 and parameters: {'learning_rate': 0.010194612403723694, 'n_estimators': 1288, 'max_depth': 14, 'subsample': 0.7106575719999109, 'colsample_bytree': 0.5775589952216353}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:12:22,775] Trial 20 finished with value: 0.8299999999999998 and parameters: {'learning_rate': 0.039205383996319294, 'n_estimators': 1736, 'max_depth': 31, 'subsample': 0.4599390729669659, 'colsample_bytree': 0.44070292574745956}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:12:24,444] Trial 21 finished with value: 0.818 and parameters: {'learning_rate': 0.08119846400997771, 'n_estimators': 154, 'max_depth': 10, 'subsample': 0.6615038737135838, 'colsample_bytree': 0.9770955924049554}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:12:28,683] Trial 22 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.08314059903303517, 'n_estimators': 834, 'max_depth': 13, 'subsample': 0.7263665061236266, 'colsample_bytree': 0.8861531683519005}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:12:30,252] Trial 23 finished with value: 0.828 and parameters: {'learning_rate': 0.03396628937622892, 'n_estimators': 472, 'max_depth': 20, 'subsample': 0.34841526255151445, 'colsample_bytree': 0.8364188625796943}. Best is trial 2 with value: 0.8379999999999999.\n",
            "[I 2023-09-21 14:12:31,626] Trial 24 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.014787086005001431, 'n_estimators': 310, 'max_depth': 7, 'subsample': 0.5034860794700338, 'colsample_bytree': 0.715345391041826}. Best is trial 24 with value: 0.8380000000000001.\n",
            "[I 2023-09-21 14:12:33,162] Trial 25 finished with value: 0.836 and parameters: {'learning_rate': 0.0149976766868348, 'n_estimators': 386, 'max_depth': 6, 'subsample': 0.5168402994048443, 'colsample_bytree': 0.6752030770105415}. Best is trial 24 with value: 0.8380000000000001.\n",
            "[I 2023-09-21 14:12:34,496] Trial 26 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.016034871741229275, 'n_estimators': 379, 'max_depth': 5, 'subsample': 0.48738382905455224, 'colsample_bytree': 0.7033915229652851}. Best is trial 26 with value: 0.8400000000000001.\n",
            "[I 2023-09-21 14:12:35,292] Trial 27 finished with value: 0.8200000000000001 and parameters: {'learning_rate': 0.0063054857260393974, 'n_estimators': 250, 'max_depth': 5, 'subsample': 0.3329036346647017, 'colsample_bytree': 0.7047861152176083}. Best is trial 26 with value: 0.8400000000000001.\n",
            "[I 2023-09-21 14:12:37,880] Trial 28 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.014926656399288571, 'n_estimators': 631, 'max_depth': 6, 'subsample': 0.467986742589809, 'colsample_bytree': 0.7254183401238631}. Best is trial 26 with value: 0.8400000000000001.\n",
            "[I 2023-09-21 14:12:42,878] Trial 29 finished with value: 0.8140000000000001 and parameters: {'learning_rate': 0.00020464054130840255, 'n_estimators': 552, 'max_depth': 6, 'subsample': 0.589783550625353, 'colsample_bytree': 0.8242888570088506}. Best is trial 26 with value: 0.8400000000000001.\n",
            "[I 2023-09-21 14:12:44,277] Trial 30 finished with value: 0.8160000000000001 and parameters: {'learning_rate': 0.0024930276632771564, 'n_estimators': 346, 'max_depth': 5, 'subsample': 0.43789601410405343, 'colsample_bytree': 0.6102697487894073}. Best is trial 26 with value: 0.8400000000000001.\n",
            "[I 2023-09-21 14:12:46,529] Trial 31 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.018340742901004507, 'n_estimators': 618, 'max_depth': 8, 'subsample': 0.46636303752315644, 'colsample_bytree': 0.6991554785618994}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:12:48,961] Trial 32 finished with value: 0.836 and parameters: {'learning_rate': 0.021301040511592408, 'n_estimators': 654, 'max_depth': 6, 'subsample': 0.5023363169910031, 'colsample_bytree': 0.7284513086353801}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:12:51,882] Trial 33 finished with value: 0.828 and parameters: {'learning_rate': 0.009059975835052081, 'n_estimators': 879, 'max_depth': 8, 'subsample': 0.3919662804027034, 'colsample_bytree': 0.6907548180714367}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:12:53,104] Trial 34 finished with value: 0.844 and parameters: {'learning_rate': 0.02408882999729634, 'n_estimators': 284, 'max_depth': 9, 'subsample': 0.47605916735033144, 'colsample_bytree': 0.7197988208844949}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:12:56,959] Trial 35 finished with value: 0.834 and parameters: {'learning_rate': 0.03856360174980399, 'n_estimators': 729, 'max_depth': 9, 'subsample': 0.4410541599350893, 'colsample_bytree': 0.784196289824763}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:13:01,156] Trial 36 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.019484180412049204, 'n_estimators': 572, 'max_depth': 9, 'subsample': 0.6030536392046821, 'colsample_bytree': 0.8000629290268209}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:13:01,531] Trial 37 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.04946858618719758, 'n_estimators': 59, 'max_depth': 7, 'subsample': 0.5643689392748602, 'colsample_bytree': 0.7459919189878053}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:13:02,880] Trial 38 finished with value: 0.836 and parameters: {'learning_rate': 0.02611312936573984, 'n_estimators': 310, 'max_depth': 6, 'subsample': 0.4574228439127201, 'colsample_bytree': 0.8959510663434012}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:13:05,803] Trial 39 finished with value: 0.836 and parameters: {'learning_rate': 0.01052406356778601, 'n_estimators': 975, 'max_depth': 13, 'subsample': 0.34542846194501825, 'colsample_bytree': 0.672304203552307}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:13:13,070] Trial 40 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.0044264824913259615, 'n_estimators': 1564, 'max_depth': 5, 'subsample': 0.5394928807620387, 'colsample_bytree': 0.7742554098475405}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:13:20,970] Trial 41 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.0051594983485934755, 'n_estimators': 1588, 'max_depth': 5, 'subsample': 0.5331971818438371, 'colsample_bytree': 0.7700564806170103}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:13:25,789] Trial 42 finished with value: 0.844 and parameters: {'learning_rate': 0.010658910020173225, 'n_estimators': 1526, 'max_depth': 7, 'subsample': 0.39624898538119074, 'colsample_bytree': 0.7426398931784033}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:13:35,961] Trial 43 finished with value: 0.836 and parameters: {'learning_rate': 0.009700398865382188, 'n_estimators': 2313, 'max_depth': 7, 'subsample': 0.4026674391845152, 'colsample_bytree': 0.7290623221012058}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:13:40,530] Trial 44 finished with value: 0.8280000000000001 and parameters: {'learning_rate': 0.020779483552886252, 'n_estimators': 1921, 'max_depth': 6, 'subsample': 0.2801372930328393, 'colsample_bytree': 0.821536125763373}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:13:43,854] Trial 45 finished with value: 0.8220000000000001 and parameters: {'learning_rate': 0.054884134886841886, 'n_estimators': 1191, 'max_depth': 8, 'subsample': 0.48114415714689385, 'colsample_bytree': 0.5907306321054437}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:13:49,213] Trial 46 finished with value: 0.836 and parameters: {'learning_rate': 0.013397979387417425, 'n_estimators': 818, 'max_depth': 7, 'subsample': 0.4788279314702133, 'colsample_bytree': 0.6292689827699094}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:13:54,570] Trial 47 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.006666449596818248, 'n_estimators': 1346, 'max_depth': 10, 'subsample': 0.42233364158447645, 'colsample_bytree': 0.8682975201526726}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:13:55,293] Trial 48 finished with value: 0.828 and parameters: {'learning_rate': 0.056347575592205136, 'n_estimators': 207, 'max_depth': 8, 'subsample': 0.3839662118242661, 'colsample_bytree': 0.6700101070374943}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:13:57,398] Trial 49 finished with value: 0.826 and parameters: {'learning_rate': 0.03311784823628584, 'n_estimators': 601, 'max_depth': 9, 'subsample': 0.4729097168453771, 'colsample_bytree': 0.7373057123187259}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:13:59,348] Trial 50 finished with value: 0.836 and parameters: {'learning_rate': 0.017643048451764988, 'n_estimators': 415, 'max_depth': 12, 'subsample': 0.5353663354834619, 'colsample_bytree': 0.8092712864184068}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:14:08,149] Trial 51 finished with value: 0.836 and parameters: {'learning_rate': 0.011525151877920768, 'n_estimators': 1567, 'max_depth': 5, 'subsample': 0.5359989196263234, 'colsample_bytree': 0.7791901940508381}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:14:13,419] Trial 52 finished with value: 0.836 and parameters: {'learning_rate': 0.004209924756306242, 'n_estimators': 1474, 'max_depth': 6, 'subsample': 0.4301201655553268, 'colsample_bytree': 0.7538621956472562}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:14:23,049] Trial 53 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.008149185181696515, 'n_estimators': 1761, 'max_depth': 5, 'subsample': 0.6220340518194367, 'colsample_bytree': 0.7069568736593822}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:14:28,165] Trial 54 finished with value: 0.828 and parameters: {'learning_rate': 0.024008128641484713, 'n_estimators': 1640, 'max_depth': 7, 'subsample': 0.5759073179610523, 'colsample_bytree': 0.660516976930633}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:14:38,262] Trial 55 finished with value: 0.828 and parameters: {'learning_rate': 0.013221514181982547, 'n_estimators': 1978, 'max_depth': 6, 'subsample': 0.559712099615628, 'colsample_bytree': 0.85668010051382}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:14:43,866] Trial 56 finished with value: 0.8219999999999998 and parameters: {'learning_rate': 0.03076361989482649, 'n_estimators': 2221, 'max_depth': 5, 'subsample': 0.48142788902093814, 'colsample_bytree': 0.6146184979792826}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:14:51,376] Trial 57 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.007462782514998279, 'n_estimators': 1422, 'max_depth': 7, 'subsample': 0.6255447997783641, 'colsample_bytree': 0.7846143983999051}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:14:57,320] Trial 58 finished with value: 0.8280000000000001 and parameters: {'learning_rate': 0.0031806590420368638, 'n_estimators': 947, 'max_depth': 8, 'subsample': 0.5089457992078406, 'colsample_bytree': 0.7106600464945848}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:15:01,141] Trial 59 finished with value: 0.8300000000000001 and parameters: {'learning_rate': 0.005200900072009587, 'n_estimators': 1121, 'max_depth': 10, 'subsample': 0.4198160421445313, 'colsample_bytree': 0.5408390063887403}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:15:06,669] Trial 60 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.016630458540082434, 'n_estimators': 1882, 'max_depth': 16, 'subsample': 0.36788941715010764, 'colsample_bytree': 0.6827987564175737}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:15:15,308] Trial 61 finished with value: 0.842 and parameters: {'learning_rate': 0.005018581800929156, 'n_estimators': 1662, 'max_depth': 5, 'subsample': 0.5406324758753654, 'colsample_bytree': 0.7624428577764562}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:15:20,062] Trial 62 finished with value: 0.844 and parameters: {'learning_rate': 0.007094070409546799, 'n_estimators': 1284, 'max_depth': 5, 'subsample': 0.5502017330371959, 'colsample_bytree': 0.7548690912351235}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:15:23,706] Trial 63 finished with value: 0.834 and parameters: {'learning_rate': 0.007381794687072451, 'n_estimators': 737, 'max_depth': 6, 'subsample': 0.4502047841157415, 'colsample_bytree': 0.7409466009037201}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:15:26,887] Trial 64 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.0113495620509781, 'n_estimators': 494, 'max_depth': 5, 'subsample': 0.49929486867272865, 'colsample_bytree': 0.6444560883516156}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:15:29,207] Trial 65 finished with value: 0.8299999999999998 and parameters: {'learning_rate': 0.04232802526008152, 'n_estimators': 408, 'max_depth': 6, 'subsample': 0.600011751416294, 'colsample_bytree': 0.8346376193762735}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:15:33,362] Trial 66 finished with value: 0.8300000000000001 and parameters: {'learning_rate': 0.023085523729576157, 'n_estimators': 1267, 'max_depth': 7, 'subsample': 0.5530012990383826, 'colsample_bytree': 0.6989264919000008}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:15:34,223] Trial 67 finished with value: 0.8280000000000001 and parameters: {'learning_rate': 0.01732869435409288, 'n_estimators': 203, 'max_depth': 11, 'subsample': 0.40984195105324195, 'colsample_bytree': 0.7976304718250431}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:15:40,730] Trial 68 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.00911746319922157, 'n_estimators': 1692, 'max_depth': 5, 'subsample': 0.4588414176718876, 'colsample_bytree': 0.7572503275961984}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:15:44,937] Trial 69 finished with value: 0.8299999999999998 and parameters: {'learning_rate': 0.028175101946903747, 'n_estimators': 672, 'max_depth': 45, 'subsample': 0.5167492183541559, 'colsample_bytree': 0.6549297765415075}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:15:48,833] Trial 70 finished with value: 0.8139999999999998 and parameters: {'learning_rate': 0.06708451510753378, 'n_estimators': 1824, 'max_depth': 9, 'subsample': 0.37047497884492797, 'colsample_bytree': 0.7158443912109451}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:15:54,378] Trial 71 finished with value: 0.842 and parameters: {'learning_rate': 0.004828174758867627, 'n_estimators': 1470, 'max_depth': 5, 'subsample': 0.5376728201786027, 'colsample_bytree': 0.7584385065503918}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:16:03,176] Trial 72 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.006383718095360433, 'n_estimators': 1417, 'max_depth': 5, 'subsample': 0.576301370955519, 'colsample_bytree': 0.8068900667377609}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:16:07,058] Trial 73 finished with value: 0.844 and parameters: {'learning_rate': 0.013475292480076173, 'n_estimators': 1079, 'max_depth': 6, 'subsample': 0.4887286617235735, 'colsample_bytree': 0.7569488500418783}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:16:12,209] Trial 74 finished with value: 0.826 and parameters: {'learning_rate': 0.0020674789892292196, 'n_estimators': 1180, 'max_depth': 6, 'subsample': 0.49253429959412565, 'colsample_bytree': 0.7683712513436993}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:16:19,424] Trial 75 finished with value: 0.8280000000000001 and parameters: {'learning_rate': 0.0032775142303872857, 'n_estimators': 1327, 'max_depth': 5, 'subsample': 0.439627831022976, 'colsample_bytree': 0.6864319131805171}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:16:23,894] Trial 76 finished with value: 0.834 and parameters: {'learning_rate': 0.013489329285575419, 'n_estimators': 1052, 'max_depth': 15, 'subsample': 0.5215706702801509, 'colsample_bytree': 0.8308501312877464}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:16:31,915] Trial 77 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.00524741021086096, 'n_estimators': 1460, 'max_depth': 8, 'subsample': 0.5528802943411659, 'colsample_bytree': 0.7453676554319191}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:16:38,086] Trial 78 finished with value: 0.842 and parameters: {'learning_rate': 0.010566265620911158, 'n_estimators': 1239, 'max_depth': 35, 'subsample': 0.463364883683972, 'colsample_bytree': 0.8517454836242165}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:16:44,992] Trial 79 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.00881478553534019, 'n_estimators': 1650, 'max_depth': 26, 'subsample': 0.4605281870179363, 'colsample_bytree': 0.921499230191512}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:16:52,993] Trial 80 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.011974554738417518, 'n_estimators': 1239, 'max_depth': 20, 'subsample': 0.5175435993539464, 'colsample_bytree': 0.8484176899911372}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:16:58,201] Trial 81 finished with value: 0.826 and parameters: {'learning_rate': 0.019123845532504423, 'n_estimators': 1511, 'max_depth': 22, 'subsample': 0.49453651097998386, 'colsample_bytree': 0.8071054346273115}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:17:04,685] Trial 82 finished with value: 0.8360000000000001 and parameters: {'learning_rate': 0.006980830131762893, 'n_estimators': 1357, 'max_depth': 18, 'subsample': 0.42536370255191186, 'colsample_bytree': 0.7581586116180614}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:17:10,060] Trial 83 finished with value: 0.842 and parameters: {'learning_rate': 0.01030029898618068, 'n_estimators': 1055, 'max_depth': 46, 'subsample': 0.4833473972626327, 'colsample_bytree': 0.7232858271868362}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:17:14,466] Trial 84 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.00988362187016769, 'n_estimators': 1035, 'max_depth': 35, 'subsample': 0.5453716575223921, 'colsample_bytree': 0.7295192276108371}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:17:21,252] Trial 85 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.005646566389930821, 'n_estimators': 1192, 'max_depth': 29, 'subsample': 0.4711739960032688, 'colsample_bytree': 0.7766056538899426}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:17:26,336] Trial 86 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.01131765393901746, 'n_estimators': 1153, 'max_depth': 44, 'subsample': 0.4012405745245482, 'colsample_bytree': 0.7892478054640815}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:17:30,220] Trial 87 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.004303938137978843, 'n_estimators': 954, 'max_depth': 50, 'subsample': 0.44516060586828515, 'colsample_bytree': 0.7197102892044115}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:17:33,349] Trial 88 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.023510690971538302, 'n_estimators': 867, 'max_depth': 35, 'subsample': 0.5335289423156256, 'colsample_bytree': 0.6873259221068081}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:17:42,518] Trial 89 finished with value: 0.8360000000000001 and parameters: {'learning_rate': 0.00808458497606621, 'n_estimators': 1279, 'max_depth': 48, 'subsample': 0.5920611706721756, 'colsample_bytree': 0.8214535832498944}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:17:47,891] Trial 90 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.015594803772613922, 'n_estimators': 1405, 'max_depth': 38, 'subsample': 0.5747040052575192, 'colsample_bytree': 0.7508486324629721}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:17:51,520] Trial 91 finished with value: 0.8360000000000001 and parameters: {'learning_rate': 0.01422525869959268, 'n_estimators': 777, 'max_depth': 40, 'subsample': 0.4877262770872681, 'colsample_bytree': 0.6974481703689392}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:17:54,072] Trial 92 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.01935393155111709, 'n_estimators': 285, 'max_depth': 13, 'subsample': 0.5165036079705327, 'colsample_bytree': 0.7336409033947144}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:18:00,591] Trial 93 finished with value: 0.8440000000000001 and parameters: {'learning_rate': 0.00977882013470039, 'n_estimators': 1538, 'max_depth': 43, 'subsample': 0.4660417051153504, 'colsample_bytree': 0.6573036632468182}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:18:05,804] Trial 94 finished with value: 0.842 and parameters: {'learning_rate': 0.0103322671670051, 'n_estimators': 1514, 'max_depth': 43, 'subsample': 0.4477506169716928, 'colsample_bytree': 0.6737368786945667}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:18:14,961] Trial 95 finished with value: 0.844 and parameters: {'learning_rate': 0.006463786710963961, 'n_estimators': 1615, 'max_depth': 41, 'subsample': 0.4700404076630142, 'colsample_bytree': 0.6494431028664871}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:18:21,353] Trial 96 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.006270470673502297, 'n_estimators': 1811, 'max_depth': 42, 'subsample': 0.42604731321991074, 'colsample_bytree': 0.6483596817462766}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:18:29,671] Trial 97 finished with value: 0.834 and parameters: {'learning_rate': 0.004667842319019145, 'n_estimators': 1546, 'max_depth': 37, 'subsample': 0.4078252688942691, 'colsample_bytree': 0.6646174398109599}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:18:35,689] Trial 98 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.0034526642782780324, 'n_estimators': 1612, 'max_depth': 33, 'subsample': 0.46787593906062885, 'colsample_bytree': 0.6381711728140864}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:18:43,149] Trial 99 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.007377850468435732, 'n_estimators': 1691, 'max_depth': 41, 'subsample': 0.5050929765640891, 'colsample_bytree': 0.6162914128391137}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:18:50,287] Trial 100 finished with value: 0.82 and parameters: {'learning_rate': 0.026933094944749675, 'n_estimators': 1719, 'max_depth': 45, 'subsample': 0.5638834358508242, 'colsample_bytree': 0.7682776402173408}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:18:54,346] Trial 101 finished with value: 0.842 and parameters: {'learning_rate': 0.01204616924625214, 'n_estimators': 1067, 'max_depth': 39, 'subsample': 0.47952079556459465, 'colsample_bytree': 0.7092268930760126}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:19:02,079] Trial 102 finished with value: 0.842 and parameters: {'learning_rate': 0.009003600365599749, 'n_estimators': 1322, 'max_depth': 47, 'subsample': 0.4591172298043762, 'colsample_bytree': 0.7908085296867225}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:19:06,566] Trial 103 finished with value: 0.834 and parameters: {'learning_rate': 0.005912934121074634, 'n_estimators': 911, 'max_depth': 41, 'subsample': 0.5299904075278937, 'colsample_bytree': 0.7290815545375704}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:19:11,601] Trial 104 finished with value: 0.8300000000000001 and parameters: {'learning_rate': 0.01596795691765066, 'n_estimators': 1498, 'max_depth': 43, 'subsample': 0.5083970937874783, 'colsample_bytree': 0.6883456253459683}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:19:20,052] Trial 105 finished with value: 0.842 and parameters: {'learning_rate': 0.007898059875762939, 'n_estimators': 1354, 'max_depth': 50, 'subsample': 0.4903742647205249, 'colsample_bytree': 0.7493223081078809}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:19:24,654] Trial 106 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.013175750231460991, 'n_estimators': 1438, 'max_depth': 46, 'subsample': 0.43489519899033163, 'colsample_bytree': 0.6621397123417597}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:19:39,961] Trial 107 finished with value: 0.844 and parameters: {'learning_rate': 0.003941827581573233, 'n_estimators': 2983, 'max_depth': 46, 'subsample': 0.5453250559633178, 'colsample_bytree': 0.715357036713831}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:19:50,212] Trial 108 finished with value: 0.844 and parameters: {'learning_rate': 0.004008503106589634, 'n_estimators': 1990, 'max_depth': 38, 'subsample': 0.5568290451700646, 'colsample_bytree': 0.7024527006406917}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:19:59,740] Trial 109 finished with value: 0.836 and parameters: {'learning_rate': 0.0029313036283142614, 'n_estimators': 1959, 'max_depth': 37, 'subsample': 0.5513660068712929, 'colsample_bytree': 0.7039037395921449}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:20:14,826] Trial 110 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.003651510645354475, 'n_estimators': 2924, 'max_depth': 32, 'subsample': 0.6165350865550673, 'colsample_bytree': 0.6302404654758895}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:20:28,114] Trial 111 finished with value: 0.842 and parameters: {'learning_rate': 0.004261110728356948, 'n_estimators': 2426, 'max_depth': 42, 'subsample': 0.5298557969123499, 'colsample_bytree': 0.7642913969657602}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:20:44,236] Trial 112 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.002685555095970647, 'n_estimators': 2827, 'max_depth': 39, 'subsample': 0.5914029281010498, 'colsample_bytree': 0.7413914011558604}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:20:55,897] Trial 113 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.005316672501347852, 'n_estimators': 2614, 'max_depth': 48, 'subsample': 0.563041680079066, 'colsample_bytree': 0.6774045836371401}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:21:03,913] Trial 114 finished with value: 0.842 and parameters: {'learning_rate': 0.006362934148611676, 'n_estimators': 1612, 'max_depth': 37, 'subsample': 0.5483166424831555, 'colsample_bytree': 0.7147280584230173}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:21:12,846] Trial 115 finished with value: 0.834 and parameters: {'learning_rate': 0.003796053172540265, 'n_estimators': 1829, 'max_depth': 44, 'subsample': 0.5193417063397153, 'colsample_bytree': 0.5886454009434411}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:21:23,034] Trial 116 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.004541780565595682, 'n_estimators': 2181, 'max_depth': 41, 'subsample': 0.5026274759967208, 'colsample_bytree': 0.7683135214216972}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:21:36,375] Trial 117 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.0021948809894568873, 'n_estimators': 2089, 'max_depth': 41, 'subsample': 0.4991419985346815, 'colsample_bytree': 0.7736779616959917}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:21:47,114] Trial 118 finished with value: 0.828 and parameters: {'learning_rate': 0.001370622760943884, 'n_estimators': 1784, 'max_depth': 43, 'subsample': 0.5757467118378623, 'colsample_bytree': 0.6969598048211578}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:21:58,063] Trial 119 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.004671025349285294, 'n_estimators': 2242, 'max_depth': 40, 'subsample': 0.5395856779261997, 'colsample_bytree': 0.7843989220231078}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:22:11,564] Trial 120 finished with value: 0.834 and parameters: {'learning_rate': 0.003183988918168591, 'n_estimators': 2017, 'max_depth': 31, 'subsample': 0.6048349573668901, 'colsample_bytree': 0.7496737180527884}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:22:24,023] Trial 121 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.008285637091595972, 'n_estimators': 2443, 'max_depth': 34, 'subsample': 0.46610552654554166, 'colsample_bytree': 0.7951887937718032}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:22:30,183] Trial 122 finished with value: 0.844 and parameters: {'learning_rate': 0.006710148595686412, 'n_estimators': 1392, 'max_depth': 36, 'subsample': 0.4506192979592438, 'colsample_bytree': 0.818969169426915}. Best is trial 31 with value: 0.8459999999999999.\n",
            "[I 2023-09-21 14:22:41,616] Trial 123 finished with value: 0.8479999999999999 and parameters: {'learning_rate': 0.005353997622431811, 'n_estimators': 2147, 'max_depth': 45, 'subsample': 0.4464811566104461, 'colsample_bytree': 0.7349022992050447}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:22:50,332] Trial 124 finished with value: 0.844 and parameters: {'learning_rate': 0.006815240135446975, 'n_estimators': 2337, 'max_depth': 45, 'subsample': 0.38588722433145783, 'colsample_bytree': 0.7227888782466527}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:23:00,506] Trial 125 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.006006884486295534, 'n_estimators': 2224, 'max_depth': 46, 'subsample': 0.38844373284626266, 'colsample_bytree': 0.7290024571317223}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:23:10,234] Trial 126 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.007037264309550695, 'n_estimators': 2359, 'max_depth': 50, 'subsample': 0.43699883283318824, 'colsample_bytree': 0.6753013344371658}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:23:19,868] Trial 127 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.0025503136850194706, 'n_estimators': 2114, 'max_depth': 44, 'subsample': 0.4196936263408766, 'colsample_bytree': 0.6520051378247202}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:23:32,580] Trial 128 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.004074131150014055, 'n_estimators': 2641, 'max_depth': 38, 'subsample': 0.40082071441748535, 'colsample_bytree': 0.714766287353525}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:23:41,446] Trial 129 finished with value: 0.836 and parameters: {'learning_rate': 0.008763747664012538, 'n_estimators': 2165, 'max_depth': 47, 'subsample': 0.44654177374317566, 'colsample_bytree': 0.8131014622918556}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:23:51,061] Trial 130 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.006915524483607144, 'n_estimators': 2164, 'max_depth': 41, 'subsample': 0.38532668466636755, 'colsample_bytree': 0.7360732396761159}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:24:02,248] Trial 131 finished with value: 0.844 and parameters: {'learning_rate': 0.005331316458651864, 'n_estimators': 2300, 'max_depth': 36, 'subsample': 0.47868704363705505, 'colsample_bytree': 0.6939791278023755}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:24:10,427] Trial 132 finished with value: 0.844 and parameters: {'learning_rate': 0.005405855921901607, 'n_estimators': 2039, 'max_depth': 36, 'subsample': 0.47962828559945453, 'colsample_bytree': 0.6928741192628416}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:24:22,008] Trial 133 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.003833377663237704, 'n_estimators': 2285, 'max_depth': 45, 'subsample': 0.41617358935193033, 'colsample_bytree': 0.7049552699459438}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:24:22,384] Trial 134 finished with value: 0.82 and parameters: {'learning_rate': 0.009785503201805622, 'n_estimators': 58, 'max_depth': 39, 'subsample': 0.45385225828676246, 'colsample_bytree': 0.6608224217570202}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:24:31,553] Trial 135 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.012845732680594999, 'n_estimators': 2546, 'max_depth': 36, 'subsample': 0.5004698573150231, 'colsample_bytree': 0.7219443002105846}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:24:39,954] Trial 136 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.020036426710294177, 'n_estimators': 2358, 'max_depth': 40, 'subsample': 0.36733787634258697, 'colsample_bytree': 0.7458719148548603}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:24:48,343] Trial 137 finished with value: 0.844 and parameters: {'learning_rate': 0.005935219882072355, 'n_estimators': 1902, 'max_depth': 33, 'subsample': 0.4809540358928762, 'colsample_bytree': 0.6851022910498511}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:25:01,559] Trial 138 finished with value: 0.844 and parameters: {'learning_rate': 0.004946135810435608, 'n_estimators': 2996, 'max_depth': 48, 'subsample': 0.43256871673555564, 'colsample_bytree': 0.7741454120009899}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:25:12,933] Trial 139 finished with value: 0.844 and parameters: {'learning_rate': 0.007276260727302134, 'n_estimators': 2463, 'max_depth': 43, 'subsample': 0.46631689297807377, 'colsample_bytree': 0.6271479480691685}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:25:25,599] Trial 140 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.0029316069468364016, 'n_estimators': 2171, 'max_depth': 38, 'subsample': 0.512138060624336, 'colsample_bytree': 0.8053123654386781}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:25:33,456] Trial 141 finished with value: 0.842 and parameters: {'learning_rate': 0.005372064623398157, 'n_estimators': 2012, 'max_depth': 42, 'subsample': 0.4803693615284104, 'colsample_bytree': 0.7036644355034493}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:25:44,217] Trial 142 finished with value: 0.842 and parameters: {'learning_rate': 0.004245977305317092, 'n_estimators': 2030, 'max_depth': 35, 'subsample': 0.4470633425721791, 'colsample_bytree': 0.6844546216903837}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:25:54,730] Trial 143 finished with value: 0.8299999999999998 and parameters: {'learning_rate': 0.008203336264739134, 'n_estimators': 2739, 'max_depth': 37, 'subsample': 0.49422082015267216, 'colsample_bytree': 0.7351536927029593}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:26:03,792] Trial 144 finished with value: 0.844 and parameters: {'learning_rate': 0.006116615468048147, 'n_estimators': 2078, 'max_depth': 29, 'subsample': 0.41285044533276966, 'colsample_bytree': 0.6955173661648515}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:26:12,848] Trial 145 finished with value: 0.834 and parameters: {'learning_rate': 0.010758338049690105, 'n_estimators': 2273, 'max_depth': 39, 'subsample': 0.4696991347000735, 'colsample_bytree': 0.6639143656623196}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:26:20,650] Trial 146 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.016536513233854168, 'n_estimators': 2350, 'max_depth': 45, 'subsample': 0.4313898763476078, 'colsample_bytree': 0.6439144709120982}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:26:33,081] Trial 147 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.003623726690244775, 'n_estimators': 2137, 'max_depth': 36, 'subsample': 0.5228359667700777, 'colsample_bytree': 0.756218722979364}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:26:38,610] Trial 148 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.00890638356734637, 'n_estimators': 1393, 'max_depth': 41, 'subsample': 0.49439937091199004, 'colsample_bytree': 0.7190598230498124}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:26:40,742] Trial 149 finished with value: 0.826 and parameters: {'learning_rate': 0.004939072225870084, 'n_estimators': 515, 'max_depth': 34, 'subsample': 0.4509091956704582, 'colsample_bytree': 0.6817055384261878}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:26:50,033] Trial 150 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.012497988542563612, 'n_estimators': 1871, 'max_depth': 49, 'subsample': 0.47534212097320805, 'colsample_bytree': 0.6045913695343514}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:26:57,595] Trial 151 finished with value: 0.844 and parameters: {'learning_rate': 0.005913964784762986, 'n_estimators': 1968, 'max_depth': 33, 'subsample': 0.47990736849590543, 'colsample_bytree': 0.6926695790206642}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:27:09,575] Trial 152 finished with value: 0.834 and parameters: {'learning_rate': 0.006844193380424411, 'n_estimators': 2206, 'max_depth': 36, 'subsample': 0.5137231383477716, 'colsample_bytree': 0.7150932846580755}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:27:18,433] Trial 153 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.004501255673614794, 'n_estimators': 1916, 'max_depth': 38, 'subsample': 0.48566729030693223, 'colsample_bytree': 0.6666752441612557}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:27:27,966] Trial 154 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.0056937859158553575, 'n_estimators': 2079, 'max_depth': 32, 'subsample': 0.4484364791716005, 'colsample_bytree': 0.7396455715045434}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:27:37,161] Trial 155 finished with value: 0.834 and parameters: {'learning_rate': 0.007961337891069922, 'n_estimators': 2068, 'max_depth': 24, 'subsample': 0.41048992806713713, 'colsample_bytree': 0.7394049745377709}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:27:44,370] Trial 156 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.0032824546948743475, 'n_estimators': 1571, 'max_depth': 12, 'subsample': 0.4528468917275489, 'colsample_bytree': 0.7576698641943441}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:27:54,387] Trial 157 finished with value: 0.836 and parameters: {'learning_rate': 0.009826458408216472, 'n_estimators': 2325, 'max_depth': 42, 'subsample': 0.39822239807883875, 'colsample_bytree': 0.7882630515961339}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:27:55,464] Trial 158 finished with value: 0.828 and parameters: {'learning_rate': 0.01438510602240112, 'n_estimators': 153, 'max_depth': 31, 'subsample': 0.43717547900493514, 'colsample_bytree': 0.7273263749345645}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:28:00,946] Trial 159 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.023210660624277926, 'n_estimators': 2112, 'max_depth': 44, 'subsample': 0.3276991824837049, 'colsample_bytree': 0.7740813028509727}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:28:13,796] Trial 160 finished with value: 0.844 and parameters: {'learning_rate': 0.005211901098821595, 'n_estimators': 2517, 'max_depth': 47, 'subsample': 0.5034991132637133, 'colsample_bytree': 0.7037827225300574}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:28:21,272] Trial 161 finished with value: 0.844 and parameters: {'learning_rate': 0.006075846321655836, 'n_estimators': 2001, 'max_depth': 36, 'subsample': 0.4723388965932551, 'colsample_bytree': 0.6797546738862491}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:28:31,449] Trial 162 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.007030749188443654, 'n_estimators': 1955, 'max_depth': 33, 'subsample': 0.45831093423076535, 'colsample_bytree': 0.6928292469145302}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:28:38,790] Trial 163 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.007804824568251595, 'n_estimators': 2054, 'max_depth': 34, 'subsample': 0.42265266082276903, 'colsample_bytree': 0.747382640461147}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:28:49,128] Trial 164 finished with value: 0.828 and parameters: {'learning_rate': 0.011405951783124348, 'n_estimators': 2209, 'max_depth': 40, 'subsample': 0.45619799307858044, 'colsample_bytree': 0.7114472624485583}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:28:58,490] Trial 165 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.003978789165448774, 'n_estimators': 1943, 'max_depth': 30, 'subsample': 0.5216266670516426, 'colsample_bytree': 0.6463181018338717}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:29:04,885] Trial 166 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.004942650567013061, 'n_estimators': 1296, 'max_depth': 37, 'subsample': 0.43687197747793904, 'colsample_bytree': 0.731677131904477}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:29:13,665] Trial 167 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.006824026504039665, 'n_estimators': 1856, 'max_depth': 33, 'subsample': 0.4627808154330894, 'colsample_bytree': 0.8256867772979491}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:29:22,393] Trial 168 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.009361300833860199, 'n_estimators': 1741, 'max_depth': 17, 'subsample': 0.5018670835075991, 'colsample_bytree': 0.7614462483798273}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:29:30,427] Trial 169 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.002384905440892953, 'n_estimators': 1520, 'max_depth': 39, 'subsample': 0.5335573550180632, 'colsample_bytree': 0.7042923694808244}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:29:39,005] Trial 170 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.002802950465596593, 'n_estimators': 2145, 'max_depth': 26, 'subsample': 0.37502860058499826, 'colsample_bytree': 0.5555735970245804}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:29:47,820] Trial 171 finished with value: 0.844 and parameters: {'learning_rate': 0.005936246447692406, 'n_estimators': 1906, 'max_depth': 33, 'subsample': 0.48128667744176096, 'colsample_bytree': 0.6898862164167306}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:29:56,884] Trial 172 finished with value: 0.844 and parameters: {'learning_rate': 0.005826355408920723, 'n_estimators': 1984, 'max_depth': 29, 'subsample': 0.4871895119552302, 'colsample_bytree': 0.6732627579377569}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:30:04,058] Trial 173 finished with value: 0.842 and parameters: {'learning_rate': 0.007162586562549995, 'n_estimators': 1479, 'max_depth': 32, 'subsample': 0.46018452410649124, 'colsample_bytree': 0.7362819546694195}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:30:12,510] Trial 174 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.004303525511938805, 'n_estimators': 1653, 'max_depth': 35, 'subsample': 0.44251934400021437, 'colsample_bytree': 0.7171782023898452}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:30:17,632] Trial 175 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.03682311205966599, 'n_estimators': 1785, 'max_depth': 28, 'subsample': 0.562711075963736, 'colsample_bytree': 0.6315255835652207}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:30:29,129] Trial 176 finished with value: 0.836 and parameters: {'learning_rate': 0.008533598746430959, 'n_estimators': 2268, 'max_depth': 31, 'subsample': 0.5070489616386903, 'colsample_bytree': 0.6936454802079666}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:30:38,127] Trial 177 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.00338195984802722, 'n_estimators': 2047, 'max_depth': 43, 'subsample': 0.41633529669463964, 'colsample_bytree': 0.6527312774151084}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:30:46,224] Trial 178 finished with value: 0.8299999999999998 and parameters: {'learning_rate': 0.018718131252140852, 'n_estimators': 2100, 'max_depth': 7, 'subsample': 0.47757839941377217, 'colsample_bytree': 0.6775718053771024}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:30:47,943] Trial 179 finished with value: 0.8299999999999998 and parameters: {'learning_rate': 0.00549862802298932, 'n_estimators': 337, 'max_depth': 8, 'subsample': 0.49547954405478406, 'colsample_bytree': 0.7801044607872343}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:30:49,882] Trial 180 finished with value: 0.826 and parameters: {'learning_rate': 0.029091375147214375, 'n_estimators': 445, 'max_depth': 46, 'subsample': 0.5265414631323138, 'colsample_bytree': 0.7448487582858339}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:31:04,346] Trial 181 finished with value: 0.844 and parameters: {'learning_rate': 0.004301329650162152, 'n_estimators': 2898, 'max_depth': 48, 'subsample': 0.43170890262579276, 'colsample_bytree': 0.7700675161447988}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:31:12,635] Trial 182 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.005186722971611369, 'n_estimators': 1400, 'max_depth': 45, 'subsample': 0.4497877561390299, 'colsample_bytree': 0.7938558951993342}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:31:22,986] Trial 183 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.007236177875437423, 'n_estimators': 2862, 'max_depth': 50, 'subsample': 0.3976466546907575, 'colsample_bytree': 0.7218153441437849}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:31:33,466] Trial 184 finished with value: 0.842 and parameters: {'learning_rate': 0.004912286521658521, 'n_estimators': 1572, 'max_depth': 41, 'subsample': 0.46697054722143405, 'colsample_bytree': 0.7695325545388423}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:31:43,513] Trial 185 finished with value: 0.8300000000000001 and parameters: {'learning_rate': 0.0018814955266457142, 'n_estimators': 2185, 'max_depth': 47, 'subsample': 0.4294819292936742, 'colsample_bytree': 0.8070876473424198}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:31:57,367] Trial 186 finished with value: 0.834 and parameters: {'learning_rate': 0.006430277732036711, 'n_estimators': 2996, 'max_depth': 10, 'subsample': 0.5461005780747262, 'colsample_bytree': 0.6966699207813959}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:32:10,408] Trial 187 finished with value: 0.826 and parameters: {'learning_rate': 0.010772092308004104, 'n_estimators': 2985, 'max_depth': 39, 'subsample': 0.45163219301302504, 'colsample_bytree': 0.7563579007067852}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:32:25,251] Trial 188 finished with value: 0.842 and parameters: {'learning_rate': 0.003844418780923059, 'n_estimators': 2803, 'max_depth': 43, 'subsample': 0.48857758447799, 'colsample_bytree': 0.7236923114568259}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:32:27,656] Trial 189 finished with value: 0.834 and parameters: {'learning_rate': 0.014783704899143773, 'n_estimators': 583, 'max_depth': 22, 'subsample': 0.47008661297644627, 'colsample_bytree': 0.661384914656978}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:32:33,953] Trial 190 finished with value: 0.834 and parameters: {'learning_rate': 0.0085710137321073, 'n_estimators': 1935, 'max_depth': 34, 'subsample': 0.43201702122275887, 'colsample_bytree': 0.5059992596646584}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:32:44,220] Trial 191 finished with value: 0.844 and parameters: {'learning_rate': 0.007122113565372043, 'n_estimators': 2254, 'max_depth': 44, 'subsample': 0.4648776055157767, 'colsample_bytree': 0.6895873876722974}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:32:54,638] Trial 192 finished with value: 0.842 and parameters: {'learning_rate': 0.005622602850038979, 'n_estimators': 2412, 'max_depth': 42, 'subsample': 0.41061039770013186, 'colsample_bytree': 0.605983163869324}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:33:06,571] Trial 193 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.004669358031587473, 'n_estimators': 2946, 'max_depth': 48, 'subsample': 0.47325315563939074, 'colsample_bytree': 0.710224855082159}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:33:15,668] Trial 194 finished with value: 0.842 and parameters: {'learning_rate': 0.004923606035195109, 'n_estimators': 1447, 'max_depth': 48, 'subsample': 0.5099512358183893, 'colsample_bytree': 0.7420101745155323}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:33:29,406] Trial 195 finished with value: 0.844 and parameters: {'learning_rate': 0.004386405326465289, 'n_estimators': 2765, 'max_depth': 50, 'subsample': 0.48797260117020663, 'colsample_bytree': 0.7139064869034205}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:33:34,116] Trial 196 finished with value: 0.834 and parameters: {'learning_rate': 0.003913975712617609, 'n_estimators': 1139, 'max_depth': 14, 'subsample': 0.4517663997893254, 'colsample_bytree': 0.7338541140284129}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:33:42,852] Trial 197 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.003308637331437579, 'n_estimators': 2045, 'max_depth': 46, 'subsample': 0.35544810799749593, 'colsample_bytree': 0.7109830343808112}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:33:52,779] Trial 198 finished with value: 0.844 and parameters: {'learning_rate': 0.0063129869703888, 'n_estimators': 2939, 'max_depth': 37, 'subsample': 0.3954862506919463, 'colsample_bytree': 0.6747090971159383}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:34:04,571] Trial 199 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.009614528455997902, 'n_estimators': 2719, 'max_depth': 40, 'subsample': 0.43380076670425044, 'colsample_bytree': 0.7606452994888836}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:34:16,843] Trial 200 finished with value: 0.828 and parameters: {'learning_rate': 0.012171247122653942, 'n_estimators': 2921, 'max_depth': 45, 'subsample': 0.5791494995707526, 'colsample_bytree': 0.7282529153758888}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:34:26,823] Trial 201 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.0076579021290903455, 'n_estimators': 2866, 'max_depth': 43, 'subsample': 0.4659645704250473, 'colsample_bytree': 0.6985278795826887}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:34:37,718] Trial 202 finished with value: 0.8460000000000001 and parameters: {'learning_rate': 0.006668228039816916, 'n_estimators': 2295, 'max_depth': 38, 'subsample': 0.4712291952131713, 'colsample_bytree': 0.6266767474430742}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:34:46,372] Trial 203 finished with value: 0.842 and parameters: {'learning_rate': 0.005119414287442331, 'n_estimators': 2292, 'max_depth': 32, 'subsample': 0.48175612550170366, 'colsample_bytree': 0.6294723900037598}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:34:56,637] Trial 204 finished with value: 0.844 and parameters: {'learning_rate': 0.00641550103517076, 'n_estimators': 2107, 'max_depth': 38, 'subsample': 0.49951323934291575, 'colsample_bytree': 0.6531055646766251}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:35:08,118] Trial 205 finished with value: 0.844 and parameters: {'learning_rate': 0.004656035869189953, 'n_estimators': 2386, 'max_depth': 9, 'subsample': 0.44586001889651883, 'colsample_bytree': 0.6682305871210805}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:35:19,937] Trial 206 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.005602612639998899, 'n_estimators': 2993, 'max_depth': 36, 'subsample': 0.5223120949225644, 'colsample_bytree': 0.6860621499053589}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:35:31,777] Trial 207 finished with value: 0.826 and parameters: {'learning_rate': 0.0007334424290385647, 'n_estimators': 2220, 'max_depth': 35, 'subsample': 0.4694102337454105, 'colsample_bytree': 0.7848389352072134}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:35:40,103] Trial 208 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.008236566055683877, 'n_estimators': 2008, 'max_depth': 38, 'subsample': 0.4182757332288893, 'colsample_bytree': 0.5815903332162085}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:35:41,621] Trial 209 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.009743333670034927, 'n_estimators': 249, 'max_depth': 48, 'subsample': 0.3822966155663045, 'colsample_bytree': 0.7437241403705904}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:35:47,253] Trial 210 finished with value: 0.836 and parameters: {'learning_rate': 0.003061781681364729, 'n_estimators': 1233, 'max_depth': 41, 'subsample': 0.5456350746790877, 'colsample_bytree': 0.7056216941000186}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:35:57,219] Trial 211 finished with value: 0.8460000000000001 and parameters: {'learning_rate': 0.0069281002928847, 'n_estimators': 2151, 'max_depth': 42, 'subsample': 0.47560474885211007, 'colsample_bytree': 0.621494092234908}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:36:04,937] Trial 212 finished with value: 0.844 and parameters: {'learning_rate': 0.006309410445086188, 'n_estimators': 2152, 'max_depth': 40, 'subsample': 0.48790173442707985, 'colsample_bytree': 0.6120430751686545}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:36:15,930] Trial 213 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.007262997904476734, 'n_estimators': 2314, 'max_depth': 44, 'subsample': 0.505789428582139, 'colsample_bytree': 0.6410428666393618}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:36:23,380] Trial 214 finished with value: 0.842 and parameters: {'learning_rate': 0.00489070189961412, 'n_estimators': 2086, 'max_depth': 7, 'subsample': 0.45477099219597805, 'colsample_bytree': 0.6589913904808757}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:36:33,446] Trial 215 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.0036408063542579753, 'n_estimators': 1883, 'max_depth': 8, 'subsample': 0.4828913820508638, 'colsample_bytree': 0.6218243429174997}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:36:39,832] Trial 216 finished with value: 0.842 and parameters: {'learning_rate': 0.005794492196676377, 'n_estimators': 2163, 'max_depth': 6, 'subsample': 0.4378986608854194, 'colsample_bytree': 0.5743460926377866}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:36:49,903] Trial 217 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.008646846100513778, 'n_estimators': 1958, 'max_depth': 46, 'subsample': 0.47060367174489337, 'colsample_bytree': 0.683642802615941}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:36:54,808] Trial 218 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.023110893384651044, 'n_estimators': 1614, 'max_depth': 34, 'subsample': 0.4486538987787861, 'colsample_bytree': 0.7218171867479413}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:37:05,167] Trial 219 finished with value: 0.834 and parameters: {'learning_rate': 0.011390589834724501, 'n_estimators': 2258, 'max_depth': 19, 'subsample': 0.5146882856553112, 'colsample_bytree': 0.6382359071486389}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:37:08,649] Trial 220 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.00678081281700362, 'n_estimators': 783, 'max_depth': 42, 'subsample': 0.42450015047158524, 'colsample_bytree': 0.8332323829922731}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:37:17,841] Trial 221 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.0077416486719770914, 'n_estimators': 2211, 'max_depth': 43, 'subsample': 0.466714767979265, 'colsample_bytree': 0.6120378786755153}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:37:26,340] Trial 222 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.007933978248947293, 'n_estimators': 2217, 'max_depth': 40, 'subsample': 0.4770276328343196, 'colsample_bytree': 0.6123940360694247}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:37:33,595] Trial 223 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.004326031611146033, 'n_estimators': 1522, 'max_depth': 48, 'subsample': 0.4600830235402555, 'colsample_bytree': 0.7005006209543745}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:37:40,370] Trial 224 finished with value: 0.8220000000000001 and parameters: {'learning_rate': 0.005778226797716286, 'n_estimators': 2120, 'max_depth': 38, 'subsample': 0.49608832261208924, 'colsample_bytree': 0.22845245915414875}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:37:45,125] Trial 225 finished with value: 0.8300000000000001 and parameters: {'learning_rate': 0.015344240324401123, 'n_estimators': 1358, 'max_depth': 44, 'subsample': 0.4730684517717559, 'colsample_bytree': 0.7516291523932779}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:37:55,555] Trial 226 finished with value: 0.8160000000000001 and parameters: {'learning_rate': 0.00022592702016191067, 'n_estimators': 2037, 'max_depth': 36, 'subsample': 0.4498005537122044, 'colsample_bytree': 0.6466450027963782}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:38:03,451] Trial 227 finished with value: 0.8160000000000001 and parameters: {'learning_rate': 1.0956125667358069e-05, 'n_estimators': 2192, 'max_depth': 32, 'subsample': 0.49820158796564457, 'colsample_bytree': 0.5921466550657318}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:38:14,618] Trial 228 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.010257457449409478, 'n_estimators': 2341, 'max_depth': 42, 'subsample': 0.5239473797337088, 'colsample_bytree': 0.6646658827866891}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:38:29,066] Trial 229 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.0071257288152346155, 'n_estimators': 2081, 'max_depth': 46, 'subsample': 0.9301318152305149, 'colsample_bytree': 0.7268983266100218}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:38:33,185] Trial 230 finished with value: 0.8300000000000001 and parameters: {'learning_rate': 0.005001805933377562, 'n_estimators': 699, 'max_depth': 30, 'subsample': 0.6839122879591908, 'colsample_bytree': 0.7726160528157467}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:38:44,068] Trial 231 finished with value: 0.842 and parameters: {'learning_rate': 0.006637430786810264, 'n_estimators': 2428, 'max_depth': 42, 'subsample': 0.46148899022787476, 'colsample_bytree': 0.6197480567566228}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:38:48,686] Trial 232 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.007966696911762668, 'n_estimators': 2563, 'max_depth': 39, 'subsample': 0.16843417184765325, 'colsample_bytree': 0.6306124017904341}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:38:59,244] Trial 233 finished with value: 0.844 and parameters: {'learning_rate': 0.005379463364884671, 'n_estimators': 2277, 'max_depth': 44, 'subsample': 0.4721125581488434, 'colsample_bytree': 0.6053775011985981}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:39:08,260] Trial 234 finished with value: 0.836 and parameters: {'learning_rate': 0.009256207361729602, 'n_estimators': 2967, 'max_depth': 50, 'subsample': 0.4398314139560744, 'colsample_bytree': 0.6818364771515371}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:39:20,661] Trial 235 finished with value: 0.842 and parameters: {'learning_rate': 0.006619867048943417, 'n_estimators': 2517, 'max_depth': 15, 'subsample': 0.4850520494352918, 'colsample_bytree': 0.7096754867312219}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:39:26,992] Trial 236 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.0174041784601564, 'n_estimators': 2136, 'max_depth': 11, 'subsample': 0.46076566624497417, 'colsample_bytree': 0.6363781066381666}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:39:38,342] Trial 237 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.004518143076115677, 'n_estimators': 2485, 'max_depth': 47, 'subsample': 0.42225810745812525, 'colsample_bytree': 0.7378130144220273}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:39:50,720] Trial 238 finished with value: 0.836 and parameters: {'learning_rate': 0.007811679228907451, 'n_estimators': 2883, 'max_depth': 10, 'subsample': 0.5023725780874291, 'colsample_bytree': 0.5935078775590779}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:39:58,621] Trial 239 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.012477554296784673, 'n_estimators': 2331, 'max_depth': 36, 'subsample': 0.5582341404574704, 'colsample_bytree': 0.6677574525271395}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:40:09,766] Trial 240 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.005963241196124481, 'n_estimators': 2201, 'max_depth': 42, 'subsample': 0.4421189322561393, 'colsample_bytree': 0.7556895752575873}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:40:19,828] Trial 241 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.0055239618168908, 'n_estimators': 2227, 'max_depth': 42, 'subsample': 0.4474939096070469, 'colsample_bytree': 0.7555772076686378}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:40:28,668] Trial 242 finished with value: 0.8479999999999999 and parameters: {'learning_rate': 0.0056381953629050215, 'n_estimators': 2160, 'max_depth': 41, 'subsample': 0.44892628768244236, 'colsample_bytree': 0.7537260660190436}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:40:39,820] Trial 243 finished with value: 0.842 and parameters: {'learning_rate': 0.0057900747832023815, 'n_estimators': 2219, 'max_depth': 41, 'subsample': 0.45267768979018325, 'colsample_bytree': 0.758017023761771}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:40:48,839] Trial 244 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.003938204082507067, 'n_estimators': 2174, 'max_depth': 39, 'subsample': 0.48051555498679743, 'colsample_bytree': 0.7427334716760277}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:40:59,707] Trial 245 finished with value: 0.8460000000000001 and parameters: {'learning_rate': 0.006280628357113299, 'n_estimators': 2248, 'max_depth': 41, 'subsample': 0.4404115457940002, 'colsample_bytree': 0.7210950566057353}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:41:09,678] Trial 246 finished with value: 0.8460000000000001 and parameters: {'learning_rate': 0.006361648076641154, 'n_estimators': 2269, 'max_depth': 41, 'subsample': 0.43913208642809565, 'colsample_bytree': 0.7219491137860475}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:41:18,088] Trial 247 finished with value: 0.842 and parameters: {'learning_rate': 0.006778736470649163, 'n_estimators': 2269, 'max_depth': 41, 'subsample': 0.4056265012405202, 'colsample_bytree': 0.7563549738676522}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:41:28,319] Trial 248 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.009398215295566776, 'n_estimators': 2223, 'max_depth': 44, 'subsample': 0.427515520902811, 'colsample_bytree': 0.7337181072840747}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:41:36,238] Trial 249 finished with value: 0.844 and parameters: {'learning_rate': 0.007782715694163429, 'n_estimators': 2313, 'max_depth': 42, 'subsample': 0.4379929660299701, 'colsample_bytree': 0.7201106443961613}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:41:45,626] Trial 250 finished with value: 0.818 and parameters: {'learning_rate': 0.02858291810820515, 'n_estimators': 2378, 'max_depth': 40, 'subsample': 0.40092407455438134, 'colsample_bytree': 0.7854130220050166}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:41:53,938] Trial 251 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.004701442228088124, 'n_estimators': 2205, 'max_depth': 43, 'subsample': 0.44734752731211425, 'colsample_bytree': 0.7473354864286503}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:42:05,758] Trial 252 finished with value: 0.844 and parameters: {'learning_rate': 0.004371490173663096, 'n_estimators': 2193, 'max_depth': 43, 'subsample': 0.44572778369200394, 'colsample_bytree': 0.7650935659683391}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:42:16,179] Trial 253 finished with value: 0.812 and parameters: {'learning_rate': 4.0511092225037264e-05, 'n_estimators': 2132, 'max_depth': 45, 'subsample': 0.4316967138618258, 'colsample_bytree': 0.7467752332794046}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:42:24,970] Trial 254 finished with value: 0.844 and parameters: {'learning_rate': 0.006150330542258069, 'n_estimators': 2241, 'max_depth': 41, 'subsample': 0.42365973334065665, 'colsample_bytree': 0.8021937195579812}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:42:37,002] Trial 255 finished with value: 0.8399999999999999 and parameters: {'learning_rate': 0.0024975830157373045, 'n_estimators': 2173, 'max_depth': 43, 'subsample': 0.45317424703731973, 'colsample_bytree': 0.729874454315583}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:42:40,816] Trial 256 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.0037466848381740034, 'n_estimators': 986, 'max_depth': 16, 'subsample': 0.3694990587411847, 'colsample_bytree': 0.7697058952675083}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:42:50,590] Trial 257 finished with value: 0.826 and parameters: {'learning_rate': 0.021522404445198366, 'n_estimators': 2229, 'max_depth': 39, 'subsample': 0.4124572273188526, 'colsample_bytree': 0.8622154033696949}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:42:57,505] Trial 258 finished with value: 0.828 and parameters: {'learning_rate': 0.013865110023816777, 'n_estimators': 2120, 'max_depth': 45, 'subsample': 0.4485703074557129, 'colsample_bytree': 0.742860953741651}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:43:03,666] Trial 259 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.00933079888228062, 'n_estimators': 1448, 'max_depth': 7, 'subsample': 0.343518477007586, 'colsample_bytree': 0.883058002272763}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:43:13,215] Trial 260 finished with value: 0.8319999999999999 and parameters: {'learning_rate': 0.00502470309032059, 'n_estimators': 2292, 'max_depth': 9, 'subsample': 0.38850520835631297, 'colsample_bytree': 0.7171255073702429}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:43:20,486] Trial 261 finished with value: 0.8219999999999998 and parameters: {'learning_rate': 0.039960938877050364, 'n_estimators': 2159, 'max_depth': 42, 'subsample': 0.5891000076985942, 'colsample_bytree': 0.7542840788645041}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:43:27,986] Trial 262 finished with value: 0.836 and parameters: {'learning_rate': 0.011161905465210276, 'n_estimators': 1558, 'max_depth': 26, 'subsample': 0.4615262556702907, 'colsample_bytree': 0.7808196940608121}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:43:36,734] Trial 263 finished with value: 0.844 and parameters: {'learning_rate': 0.006901029592345622, 'n_estimators': 2256, 'max_depth': 38, 'subsample': 0.43518969051906253, 'colsample_bytree': 0.7152953531920769}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:43:45,788] Trial 264 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.0058340073392685035, 'n_estimators': 2090, 'max_depth': 40, 'subsample': 0.4040698829394472, 'colsample_bytree': 0.7331237295926782}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:43:57,061] Trial 265 finished with value: 0.834 and parameters: {'learning_rate': 0.008318589481997119, 'n_estimators': 1698, 'max_depth': 23, 'subsample': 0.7716728185506604, 'colsample_bytree': 0.7550492421068615}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:44:06,296] Trial 266 finished with value: 0.842 and parameters: {'learning_rate': 0.003043148401013243, 'n_estimators': 2192, 'max_depth': 45, 'subsample': 0.4624396334304356, 'colsample_bytree': 0.8019808141329734}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:44:11,672] Trial 267 finished with value: 0.8099999999999999 and parameters: {'learning_rate': 0.07294397657961495, 'n_estimators': 2385, 'max_depth': 6, 'subsample': 0.108517064065356, 'colsample_bytree': 0.7022430636133099}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:44:22,532] Trial 268 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.004437247704065966, 'n_estimators': 2282, 'max_depth': 8, 'subsample': 0.5660476678448237, 'colsample_bytree': 0.7328646414075705}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:44:37,286] Trial 269 finished with value: 0.836 and parameters: {'learning_rate': 0.0013550044607839992, 'n_estimators': 2147, 'max_depth': 47, 'subsample': 0.6348822940118678, 'colsample_bytree': 0.8178464729125831}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:44:44,216] Trial 270 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.007122521624089122, 'n_estimators': 1284, 'max_depth': 43, 'subsample': 0.41782408853886616, 'colsample_bytree': 0.9192367630196082}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:44:50,484] Trial 271 finished with value: 0.8280000000000001 and parameters: {'learning_rate': 0.018074455018090293, 'n_estimators': 2220, 'max_depth': 40, 'subsample': 0.25806852184891965, 'colsample_bytree': 0.7180342980437434}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:44:57,766] Trial 272 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.005713859084542966, 'n_estimators': 1489, 'max_depth': 38, 'subsample': 0.5428115518605009, 'colsample_bytree': 0.7835843331941982}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:45:10,388] Trial 273 finished with value: 0.842 and parameters: {'learning_rate': 0.003478754940214498, 'n_estimators': 2673, 'max_depth': 12, 'subsample': 0.44367720197980015, 'colsample_bytree': 0.763503199962279}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:45:21,803] Trial 274 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.004683026732756639, 'n_estimators': 2077, 'max_depth': 42, 'subsample': 0.46557405623174786, 'colsample_bytree': 0.7476616448473697}. Best is trial 123 with value: 0.8479999999999999.\n",
            "[I 2023-09-21 14:45:29,765] Trial 275 finished with value: 0.8480000000000001 and parameters: {'learning_rate': 0.005035549297320079, 'n_estimators': 2047, 'max_depth': 14, 'subsample': 0.4665565745612098, 'colsample_bytree': 0.7465541645266434}. Best is trial 275 with value: 0.8480000000000001.\n",
            "[I 2023-09-21 14:45:40,899] Trial 276 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.004145884920549891, 'n_estimators': 1986, 'max_depth': 13, 'subsample': 0.4938433175986436, 'colsample_bytree': 0.7583542490116099}. Best is trial 275 with value: 0.8480000000000001.\n",
            "[I 2023-09-21 14:45:50,580] Trial 277 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.004795594130158524, 'n_estimators': 2059, 'max_depth': 18, 'subsample': 0.46939265974041744, 'colsample_bytree': 0.7479205148038547}. Best is trial 275 with value: 0.8480000000000001.\n",
            "[I 2023-09-21 14:45:59,448] Trial 278 finished with value: 0.85 and parameters: {'learning_rate': 0.0052493969604778335, 'n_estimators': 2063, 'max_depth': 17, 'subsample': 0.4686499286014045, 'colsample_bytree': 0.7475032992018813}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:46:10,222] Trial 279 finished with value: 0.8480000000000001 and parameters: {'learning_rate': 0.005038375028937176, 'n_estimators': 2060, 'max_depth': 17, 'subsample': 0.467700717892769, 'colsample_bytree': 0.7454875071367486}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:46:18,231] Trial 280 finished with value: 0.844 and parameters: {'learning_rate': 0.004842836680958676, 'n_estimators': 2089, 'max_depth': 17, 'subsample': 0.4686272733830717, 'colsample_bytree': 0.7445576104836332}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:46:29,413] Trial 281 finished with value: 0.8480000000000001 and parameters: {'learning_rate': 0.005156334160920844, 'n_estimators': 2041, 'max_depth': 21, 'subsample': 0.4653352556090989, 'colsample_bytree': 0.770373161948627}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:46:34,963] Trial 282 finished with value: 0.8220000000000001 and parameters: {'learning_rate': 0.0343266489848837, 'n_estimators': 2042, 'max_depth': 17, 'subsample': 0.4603612134005281, 'colsample_bytree': 0.774970097920355}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:46:43,746] Trial 283 finished with value: 0.8219999999999998 and parameters: {'learning_rate': 0.026465629975072753, 'n_estimators': 2003, 'max_depth': 21, 'subsample': 0.4418013959487267, 'colsample_bytree': 0.7692563405253386}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:46:51,795] Trial 284 finished with value: 0.844 and parameters: {'learning_rate': 0.005098746385487962, 'n_estimators': 2072, 'max_depth': 19, 'subsample': 0.4747147974616947, 'colsample_bytree': 0.7462683564006548}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:47:03,424] Trial 285 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.0046069200826268, 'n_estimators': 2059, 'max_depth': 15, 'subsample': 0.4633244187314916, 'colsample_bytree': 0.78293236357586}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:47:08,744] Trial 286 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.047326794400982274, 'n_estimators': 2057, 'max_depth': 16, 'subsample': 0.4615233229743347, 'colsample_bytree': 0.7841000241512737}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:47:20,987] Trial 287 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.003631581827695491, 'n_estimators': 2122, 'max_depth': 14, 'subsample': 0.4859184333370016, 'colsample_bytree': 0.7669961746735382}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:47:30,990] Trial 288 finished with value: 0.844 and parameters: {'learning_rate': 0.004401161253833958, 'n_estimators': 1965, 'max_depth': 17, 'subsample': 0.4410083159487178, 'colsample_bytree': 0.7972795532140641}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:47:39,911] Trial 289 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.002857897924080243, 'n_estimators': 2030, 'max_depth': 16, 'subsample': 0.4673645164460436, 'colsample_bytree': 0.7404023629208275}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:47:50,817] Trial 290 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.0053499750824029515, 'n_estimators': 2097, 'max_depth': 15, 'subsample': 0.44818025126648703, 'colsample_bytree': 0.7538417550364032}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:47:57,749] Trial 291 finished with value: 0.8460000000000001 and parameters: {'learning_rate': 0.0049702794755239295, 'n_estimators': 2109, 'max_depth': 15, 'subsample': 0.45033455684983625, 'colsample_bytree': 0.5621443260458087}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:48:07,484] Trial 292 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.005029620872459287, 'n_estimators': 2078, 'max_depth': 15, 'subsample': 0.4294072483526095, 'colsample_bytree': 0.5325511139973653}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:48:14,646] Trial 293 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.0036748303617544775, 'n_estimators': 2122, 'max_depth': 18, 'subsample': 0.44773502422626277, 'colsample_bytree': 0.5589175588730512}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:48:25,833] Trial 294 finished with value: 0.844 and parameters: {'learning_rate': 0.005530807884108332, 'n_estimators': 2033, 'max_depth': 15, 'subsample': 0.4544890712393178, 'colsample_bytree': 0.7867535809394146}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:48:32,815] Trial 295 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.004798797491320668, 'n_estimators': 2172, 'max_depth': 14, 'subsample': 0.42515788039424446, 'colsample_bytree': 0.5838714051551912}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:48:42,846] Trial 296 finished with value: 0.836 and parameters: {'learning_rate': 0.004246562097627823, 'n_estimators': 1942, 'max_depth': 16, 'subsample': 0.47591084064273304, 'colsample_bytree': 0.5715135074637163}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:48:49,462] Trial 297 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.005682214896639239, 'n_estimators': 2117, 'max_depth': 19, 'subsample': 0.4548082429119063, 'colsample_bytree': 0.5221981492022657}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:48:59,703] Trial 298 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.003208326845804253, 'n_estimators': 2010, 'max_depth': 15, 'subsample': 0.49430272204152176, 'colsample_bytree': 0.4839621923212691}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:49:06,530] Trial 299 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.005985761233640991, 'n_estimators': 2095, 'max_depth': 27, 'subsample': 0.4295253982650884, 'colsample_bytree': 0.5945654271423256}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:49:18,383] Trial 300 finished with value: 0.844 and parameters: {'learning_rate': 0.0045142146470746845, 'n_estimators': 2159, 'max_depth': 18, 'subsample': 0.47201082136153005, 'colsample_bytree': 0.7671281489683058}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:49:28,387] Trial 301 finished with value: 0.842 and parameters: {'learning_rate': 0.003840110704582872, 'n_estimators': 2063, 'max_depth': 20, 'subsample': 0.45174027370292785, 'colsample_bytree': 0.7546015251814753}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:49:35,364] Trial 302 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.0055083142124174094, 'n_estimators': 2185, 'max_depth': 14, 'subsample': 0.4391997820817125, 'colsample_bytree': 0.44605752077591937}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:49:44,653] Trial 303 finished with value: 0.8360000000000001 and parameters: {'learning_rate': 0.0021104182959000646, 'n_estimators': 2002, 'max_depth': 17, 'subsample': 0.4803579167421881, 'colsample_bytree': 0.5582944578116966}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:49:52,949] Trial 304 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.006394610490151127, 'n_estimators': 2140, 'max_depth': 16, 'subsample': 0.41653079479230487, 'colsample_bytree': 0.7344319395702448}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:50:04,121] Trial 305 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.0046630773749981, 'n_estimators': 2080, 'max_depth': 20, 'subsample': 0.4638646833382375, 'colsample_bytree': 0.7974892750079721}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:50:13,075] Trial 306 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.003334025454780992, 'n_estimators': 2060, 'max_depth': 20, 'subsample': 0.494401021466114, 'colsample_bytree': 0.7884502867495676}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:50:25,340] Trial 307 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.0025717821462753246, 'n_estimators': 2217, 'max_depth': 23, 'subsample': 0.4527372469613264, 'colsample_bytree': 0.8206241852327016}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:50:36,649] Trial 308 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.004589170652094567, 'n_estimators': 2107, 'max_depth': 25, 'subsample': 0.46695302761260066, 'colsample_bytree': 0.775098180496358}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:50:44,808] Trial 309 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.0039037441743110034, 'n_estimators': 2173, 'max_depth': 18, 'subsample': 0.4347521983833549, 'colsample_bytree': 0.7558776557900224}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:50:56,013] Trial 310 finished with value: 0.844 and parameters: {'learning_rate': 0.004979273510920474, 'n_estimators': 1983, 'max_depth': 28, 'subsample': 0.484271086040743, 'colsample_bytree': 0.8020073227750848}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:51:05,152] Trial 311 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.003092081456552243, 'n_estimators': 2080, 'max_depth': 21, 'subsample': 0.44142466277198594, 'colsample_bytree': 0.7482437114612491}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:51:15,715] Trial 312 finished with value: 0.8299999999999998 and parameters: {'learning_rate': 0.005526773994997167, 'n_estimators': 1940, 'max_depth': 17, 'subsample': 0.8383712478116125, 'colsample_bytree': 0.5669330298154533}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:51:26,167] Trial 313 finished with value: 0.8399999999999999 and parameters: {'learning_rate': 0.00429582591763366, 'n_estimators': 2240, 'max_depth': 19, 'subsample': 0.4632915322017957, 'colsample_bytree': 0.5393483290978717}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:51:36,498] Trial 314 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.0017219738008173529, 'n_estimators': 2131, 'max_depth': 12, 'subsample': 0.506055990266464, 'colsample_bytree': 0.8002426680117469}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:51:45,958] Trial 315 finished with value: 0.842 and parameters: {'learning_rate': 0.006460707190007058, 'n_estimators': 2023, 'max_depth': 24, 'subsample': 0.41466764446080245, 'colsample_bytree': 0.768109762892855}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:51:54,216] Trial 316 finished with value: 0.842 and parameters: {'learning_rate': 0.004742609140717234, 'n_estimators': 2188, 'max_depth': 16, 'subsample': 0.46218299427067555, 'colsample_bytree': 0.5427137750453723}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:52:00,223] Trial 317 finished with value: 0.836 and parameters: {'learning_rate': 0.0588573780103859, 'n_estimators': 1887, 'max_depth': 18, 'subsample': 0.4845977009358292, 'colsample_bytree': 0.5996710569446483}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:52:07,407] Trial 318 finished with value: 0.844 and parameters: {'learning_rate': 0.0073562735786482335, 'n_estimators': 2072, 'max_depth': 15, 'subsample': 0.44131682282224616, 'colsample_bytree': 0.7286585046517351}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:52:19,169] Trial 319 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.003735568490286976, 'n_estimators': 2277, 'max_depth': 19, 'subsample': 0.42211942813776193, 'colsample_bytree': 0.7868386731582714}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:52:29,819] Trial 320 finished with value: 0.842 and parameters: {'learning_rate': 0.005674947422772192, 'n_estimators': 2148, 'max_depth': 21, 'subsample': 0.5084101805005214, 'colsample_bytree': 0.7425938025499548}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:52:39,236] Trial 321 finished with value: 0.844 and parameters: {'learning_rate': 0.004911406391059689, 'n_estimators': 2215, 'max_depth': 14, 'subsample': 0.4529214279019873, 'colsample_bytree': 0.8418115240422448}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:52:49,135] Trial 322 finished with value: 0.844 and parameters: {'learning_rate': 0.007803468859645119, 'n_estimators': 2030, 'max_depth': 13, 'subsample': 0.47508883501220567, 'colsample_bytree': 0.622115632445366}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:52:56,545] Trial 323 finished with value: 0.8480000000000001 and parameters: {'learning_rate': 0.006203556693819993, 'n_estimators': 2114, 'max_depth': 17, 'subsample': 0.43803218051488063, 'colsample_bytree': 0.7231669837437983}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:53:06,677] Trial 324 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.006282478443951176, 'n_estimators': 2120, 'max_depth': 15, 'subsample': 0.40446158825114453, 'colsample_bytree': 0.713357491665191}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:53:14,337] Trial 325 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.008246400983323953, 'n_estimators': 2322, 'max_depth': 16, 'subsample': 0.4259602361848467, 'colsample_bytree': 0.7274490374477064}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:53:26,741] Trial 326 finished with value: 0.8299999999999998 and parameters: {'learning_rate': 0.006526374212709018, 'n_estimators': 1954, 'max_depth': 14, 'subsample': 0.9650398741375037, 'colsample_bytree': 0.5775787082150814}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:53:38,613] Trial 327 finished with value: 0.842 and parameters: {'learning_rate': 0.00268937292153346, 'n_estimators': 2254, 'max_depth': 18, 'subsample': 0.44848742399769953, 'colsample_bytree': 0.7507771404522534}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:53:46,704] Trial 328 finished with value: 0.842 and parameters: {'learning_rate': 0.0038676653307723, 'n_estimators': 2168, 'max_depth': 17, 'subsample': 0.4355610053502895, 'colsample_bytree': 0.7071622231444401}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:53:53,656] Trial 329 finished with value: 0.826 and parameters: {'learning_rate': 0.05362627146707076, 'n_estimators': 2202, 'max_depth': 15, 'subsample': 0.48504527730514224, 'colsample_bytree': 0.34977193380840343}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:54:00,946] Trial 330 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.0055330693003283644, 'n_estimators': 2120, 'max_depth': 30, 'subsample': 0.40821941293440217, 'colsample_bytree': 0.7340548307486144}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:54:08,391] Trial 331 finished with value: 0.828 and parameters: {'learning_rate': 0.04461845236683221, 'n_estimators': 2017, 'max_depth': 25, 'subsample': 0.49607342725820197, 'colsample_bytree': 0.7708228103724118}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:54:16,295] Trial 332 finished with value: 0.8460000000000001 and parameters: {'learning_rate': 0.007434326343710624, 'n_estimators': 2055, 'max_depth': 13, 'subsample': 0.4387524046188116, 'colsample_bytree': 0.7538234706229774}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:54:27,059] Trial 333 finished with value: 0.826 and parameters: {'learning_rate': 0.031907199818327237, 'n_estimators': 1973, 'max_depth': 13, 'subsample': 0.8776510037669751, 'colsample_bytree': 0.9550794711188304}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:54:34,387] Trial 334 finished with value: 0.842 and parameters: {'learning_rate': 0.008424614556737355, 'n_estimators': 2247, 'max_depth': 28, 'subsample': 0.42015626539311274, 'colsample_bytree': 0.7264049947802629}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:54:44,529] Trial 335 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.00737528138994496, 'n_estimators': 2056, 'max_depth': 22, 'subsample': 0.4692500767407173, 'colsample_bytree': 0.7016854987323384}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:54:51,829] Trial 336 finished with value: 0.818 and parameters: {'learning_rate': 0.0006652939512421768, 'n_estimators': 1907, 'max_depth': 27, 'subsample': 0.43683033873459426, 'colsample_bytree': 0.742067937547945}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:55:02,083] Trial 337 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.009458919846629539, 'n_estimators': 2169, 'max_depth': 42, 'subsample': 0.5094321974009115, 'colsample_bytree': 0.6101599257815651}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:55:11,455] Trial 338 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.00666863587068937, 'n_estimators': 1839, 'max_depth': 17, 'subsample': 0.6902100501066357, 'colsample_bytree': 0.7626409289796467}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:55:21,906] Trial 339 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.003398768638214004, 'n_estimators': 2137, 'max_depth': 13, 'subsample': 0.45868673699032436, 'colsample_bytree': 0.7223040534103425}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:55:30,600] Trial 340 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.0061405471254674425, 'n_estimators': 2326, 'max_depth': 16, 'subsample': 0.39079186129110166, 'colsample_bytree': 0.5543138690583944}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:55:35,749] Trial 341 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.09148044629741713, 'n_estimators': 2034, 'max_depth': 12, 'subsample': 0.4759478309950348, 'colsample_bytree': 0.7787121313623703}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:55:45,066] Trial 342 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.004111934946137149, 'n_estimators': 2232, 'max_depth': 43, 'subsample': 0.43638480549640585, 'colsample_bytree': 0.7450758787697975}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:55:51,349] Trial 343 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.06610444653511684, 'n_estimators': 2092, 'max_depth': 14, 'subsample': 0.4886469026404159, 'colsample_bytree': 0.6964218851047298}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:55:59,141] Trial 344 finished with value: 0.842 and parameters: {'learning_rate': 0.007705202627187418, 'n_estimators': 2160, 'max_depth': 40, 'subsample': 0.4554873194041945, 'colsample_bytree': 0.7205153129349451}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:56:10,011] Trial 345 finished with value: 0.844 and parameters: {'learning_rate': 0.004975273210595932, 'n_estimators': 2300, 'max_depth': 19, 'subsample': 0.4267689899986631, 'colsample_bytree': 0.7555783331514885}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:56:21,279] Trial 346 finished with value: 0.8319999999999999 and parameters: {'learning_rate': 0.011518487557862288, 'n_estimators': 1994, 'max_depth': 41, 'subsample': 0.7446886842287211, 'colsample_bytree': 0.7359108646073695}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:56:28,755] Trial 347 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.005750576736969844, 'n_estimators': 2203, 'max_depth': 45, 'subsample': 0.4724513058989491, 'colsample_bytree': 0.591300544300555}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:56:39,247] Trial 348 finished with value: 0.8299999999999998 and parameters: {'learning_rate': 0.002339234741490606, 'n_estimators': 2059, 'max_depth': 11, 'subsample': 0.5190383890373743, 'colsample_bytree': 0.512262634318446}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:56:47,076] Trial 349 finished with value: 0.844 and parameters: {'learning_rate': 0.006900951497560424, 'n_estimators': 2378, 'max_depth': 31, 'subsample': 0.41544081566135405, 'colsample_bytree': 0.7093510148395112}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:56:56,070] Trial 350 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.020393005754566016, 'n_estimators': 1948, 'max_depth': 10, 'subsample': 0.4415515405280565, 'colsample_bytree': 0.7740084247984107}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:57:00,643] Trial 351 finished with value: 0.8019999999999999 and parameters: {'learning_rate': 0.004634141293236105, 'n_estimators': 2149, 'max_depth': 39, 'subsample': 0.4571331104655913, 'colsample_bytree': 0.1481873823171857}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:57:10,548] Trial 352 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.009430800807009117, 'n_estimators': 2097, 'max_depth': 16, 'subsample': 0.4959329135842148, 'colsample_bytree': 0.6820763936956279}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:57:20,214] Trial 353 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.003082496187054569, 'n_estimators': 2259, 'max_depth': 37, 'subsample': 0.4713449823971395, 'colsample_bytree': 0.7651351681549184}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:57:31,534] Trial 354 finished with value: 0.844 and parameters: {'learning_rate': 0.0041435771538574015, 'n_estimators': 2206, 'max_depth': 34, 'subsample': 0.4458232786578318, 'colsample_bytree': 0.7332886577866867}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:57:38,866] Trial 355 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.006034596832113058, 'n_estimators': 2005, 'max_depth': 9, 'subsample': 0.4013533341322465, 'colsample_bytree': 0.7508025871592972}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:57:49,205] Trial 356 finished with value: 0.834 and parameters: {'learning_rate': 0.008159558619603203, 'n_estimators': 2113, 'max_depth': 25, 'subsample': 0.6245565533550216, 'colsample_bytree': 0.6184464623129593}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:57:53,850] Trial 357 finished with value: 0.828 and parameters: {'learning_rate': 0.005264719017808884, 'n_estimators': 2073, 'max_depth': 29, 'subsample': 0.19792411682285715, 'colsample_bytree': 0.786092190242783}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:58:06,829] Trial 358 finished with value: 0.834 and parameters: {'learning_rate': 0.001592846416206549, 'n_estimators': 2173, 'max_depth': 48, 'subsample': 0.4912736970010013, 'colsample_bytree': 0.811125605943085}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:58:18,150] Trial 359 finished with value: 0.842 and parameters: {'learning_rate': 0.00356269047461771, 'n_estimators': 2292, 'max_depth': 42, 'subsample': 0.4271696091756532, 'colsample_bytree': 0.716572799258196}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:58:24,602] Trial 360 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.006966438875760331, 'n_estimators': 2041, 'max_depth': 44, 'subsample': 0.4601567633115917, 'colsample_bytree': 0.5733028416173932}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:58:35,846] Trial 361 finished with value: 0.836 and parameters: {'learning_rate': 0.0019909842952563848, 'n_estimators': 1978, 'max_depth': 38, 'subsample': 0.4784636043729523, 'colsample_bytree': 0.6948555277612226}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:58:40,264] Trial 362 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.08133388509652338, 'n_estimators': 2127, 'max_depth': 46, 'subsample': 0.5087148258412238, 'colsample_bytree': 0.6330815832658315}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:58:48,104] Trial 363 finished with value: 0.8299999999999998 and parameters: {'learning_rate': 0.01386043895402656, 'n_estimators': 1912, 'max_depth': 18, 'subsample': 0.4444843154492632, 'colsample_bytree': 0.7416538513423095}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:58:57,056] Trial 364 finished with value: 0.836 and parameters: {'learning_rate': 0.0044490662362869325, 'n_estimators': 2230, 'max_depth': 24, 'subsample': 0.41354718672521984, 'colsample_bytree': 0.7639265407657125}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:59:10,690] Trial 365 finished with value: 0.834 and parameters: {'learning_rate': 0.009838432729476295, 'n_estimators': 2601, 'max_depth': 17, 'subsample': 0.801945957008741, 'colsample_bytree': 0.6545692103777437}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:59:19,689] Trial 366 finished with value: 0.844 and parameters: {'learning_rate': 0.005379167357176005, 'n_estimators': 2183, 'max_depth': 32, 'subsample': 0.46004374883126237, 'colsample_bytree': 0.7273748238910389}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:59:28,092] Trial 367 finished with value: 0.842 and parameters: {'learning_rate': 0.007536994390105078, 'n_estimators': 2052, 'max_depth': 41, 'subsample': 0.4766916375632365, 'colsample_bytree': 0.5425714039920125}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:59:38,594] Trial 368 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.0027524987906075308, 'n_estimators': 2113, 'max_depth': 21, 'subsample': 0.43637895044328323, 'colsample_bytree': 0.7771859258268962}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:59:47,824] Trial 369 finished with value: 0.844 and parameters: {'learning_rate': 0.005917272193213263, 'n_estimators': 2257, 'max_depth': 43, 'subsample': 0.5263848842495474, 'colsample_bytree': 0.7058155597595563}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 14:59:59,705] Trial 370 finished with value: 0.842 and parameters: {'learning_rate': 0.004272365639800923, 'n_estimators': 2427, 'max_depth': 20, 'subsample': 0.4948091348933605, 'colsample_bytree': 0.6033267025784567}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:00:06,029] Trial 371 finished with value: 0.828 and parameters: {'learning_rate': 0.00349669468526606, 'n_estimators': 2360, 'max_depth': 50, 'subsample': 0.2884185899416968, 'colsample_bytree': 0.6736189977182292}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:00:15,308] Trial 372 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.006573124283755689, 'n_estimators': 1999, 'max_depth': 11, 'subsample': 0.45362255704426685, 'colsample_bytree': 0.4932011301851641}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:00:20,413] Trial 373 finished with value: 0.82 and parameters: {'learning_rate': 0.040259889383463636, 'n_estimators': 2175, 'max_depth': 19, 'subsample': 0.38561806786527003, 'colsample_bytree': 0.7539507495859261}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:00:28,705] Trial 374 finished with value: 0.826 and parameters: {'learning_rate': 0.024699779919568884, 'n_estimators': 2061, 'max_depth': 15, 'subsample': 0.42372350243932444, 'colsample_bytree': 0.7939634966607877}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:00:39,560] Trial 375 finished with value: 0.8299999999999998 and parameters: {'learning_rate': 0.011140734418072649, 'n_estimators': 2299, 'max_depth': 14, 'subsample': 0.8732655324633212, 'colsample_bytree': 0.7341024126194688}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:00:51,372] Trial 376 finished with value: 0.8160000000000001 and parameters: {'learning_rate': 0.00034741432472062733, 'n_estimators': 2139, 'max_depth': 26, 'subsample': 0.46908069676356373, 'colsample_bytree': 0.7217820188656414}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:00:59,786] Trial 377 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.008632074661673638, 'n_estimators': 2216, 'max_depth': 17, 'subsample': 0.443016906407288, 'colsample_bytree': 0.6890979329067758}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:01:10,952] Trial 378 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.005237876673289061, 'n_estimators': 1955, 'max_depth': 18, 'subsample': 0.675646857890282, 'colsample_bytree': 0.7533092553858524}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:01:20,309] Trial 379 finished with value: 0.8140000000000001 and parameters: {'learning_rate': 0.00011570136165093684, 'n_estimators': 1851, 'max_depth': 22, 'subsample': 0.48508817930907605, 'colsample_bytree': 0.5840823092920303}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:01:27,911] Trial 380 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.004619614075660989, 'n_estimators': 2098, 'max_depth': 40, 'subsample': 0.39965693643579037, 'colsample_bytree': 0.7774137745565318}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:01:37,445] Trial 381 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.006526016577991187, 'n_estimators': 2056, 'max_depth': 37, 'subsample': 0.4610152511792734, 'colsample_bytree': 0.5248528855278471}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:01:43,914] Trial 382 finished with value: 0.8299999999999998 and parameters: {'learning_rate': 0.015307509073505303, 'n_estimators': 2146, 'max_depth': 46, 'subsample': 0.5048695304660147, 'colsample_bytree': 0.6382262881391353}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:01:55,925] Trial 383 finished with value: 0.826 and parameters: {'learning_rate': 0.0011133730733766758, 'n_estimators': 2248, 'max_depth': 15, 'subsample': 0.4281892284180215, 'colsample_bytree': 0.7384740891092394}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:02:05,590] Trial 384 finished with value: 0.8399999999999999 and parameters: {'learning_rate': 0.0023333398111706274, 'n_estimators': 2010, 'max_depth': 16, 'subsample': 0.44799932222020483, 'colsample_bytree': 0.8175055481754083}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:02:13,530] Trial 385 finished with value: 0.8160000000000001 and parameters: {'learning_rate': 0.03431329837285794, 'n_estimators': 2201, 'max_depth': 13, 'subsample': 0.4762216323823295, 'colsample_bytree': 0.8385508112776234}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:02:23,781] Trial 386 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.0038872069105673965, 'n_estimators': 2327, 'max_depth': 44, 'subsample': 0.4158245988925489, 'colsample_bytree': 0.7096372736590295}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:02:32,368] Trial 387 finished with value: 0.836 and parameters: {'learning_rate': 0.00782944906109291, 'n_estimators': 2114, 'max_depth': 28, 'subsample': 0.46407248526453415, 'colsample_bytree': 0.7631837603866789}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:02:41,470] Trial 388 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.005324896246853159, 'n_estimators': 1900, 'max_depth': 39, 'subsample': 0.4918575223576272, 'colsample_bytree': 0.5633763231188722}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:02:49,864] Trial 389 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.0030670575246920296, 'n_estimators': 2018, 'max_depth': 12, 'subsample': 0.43808620020708566, 'colsample_bytree': 0.7451530170549273}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:03:01,239] Trial 390 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.006197192898035969, 'n_estimators': 2186, 'max_depth': 42, 'subsample': 0.5182534174120954, 'colsample_bytree': 0.6734644090232597}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:03:07,590] Trial 391 finished with value: 0.826 and parameters: {'learning_rate': 0.01842225010933319, 'n_estimators': 2107, 'max_depth': 14, 'subsample': 0.45291839639189263, 'colsample_bytree': 0.7158035106514288}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:03:18,768] Trial 392 finished with value: 0.836 and parameters: {'learning_rate': 0.004543010714644741, 'n_estimators': 2247, 'max_depth': 16, 'subsample': 0.3651835697750972, 'colsample_bytree': 0.874763040820883}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:03:27,499] Trial 393 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.009658338997374557, 'n_estimators': 2064, 'max_depth': 31, 'subsample': 0.4752979130512188, 'colsample_bytree': 0.9030878151187696}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:03:35,956] Trial 394 finished with value: 0.842 and parameters: {'learning_rate': 0.007294821913001782, 'n_estimators': 1958, 'max_depth': 35, 'subsample': 0.430962782622269, 'colsample_bytree': 0.6086796007543939}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:03:41,583] Trial 395 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.005275548637197793, 'n_estimators': 2167, 'max_depth': 23, 'subsample': 0.41319980397264033, 'colsample_bytree': 0.3910942608384126}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:03:54,300] Trial 396 finished with value: 0.844 and parameters: {'learning_rate': 0.004340475097625985, 'n_estimators': 2315, 'max_depth': 47, 'subsample': 0.49280836059283156, 'colsample_bytree': 0.7857183706957436}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:04:05,066] Trial 397 finished with value: 0.836 and parameters: {'learning_rate': 0.012235481141010132, 'n_estimators': 2129, 'max_depth': 33, 'subsample': 0.7086681295886188, 'colsample_bytree': 0.6481420082221124}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:04:08,858] Trial 398 finished with value: 0.7979999999999999 and parameters: {'learning_rate': 0.0014838011144860412, 'n_estimators': 2017, 'max_depth': 41, 'subsample': 0.11363373862586218, 'colsample_bytree': 0.695284006305787}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:04:17,832] Trial 399 finished with value: 0.844 and parameters: {'learning_rate': 0.006126381454674082, 'n_estimators': 2260, 'max_depth': 39, 'subsample': 0.4561673548092116, 'colsample_bytree': 0.7639471253581167}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:04:28,214] Trial 400 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.003638972117816836, 'n_estimators': 2063, 'max_depth': 30, 'subsample': 0.4735344889873412, 'colsample_bytree': 0.7291709012425599}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:04:38,686] Trial 401 finished with value: 0.8460000000000001 and parameters: {'learning_rate': 0.008307009310369678, 'n_estimators': 2167, 'max_depth': 17, 'subsample': 0.4413294017155694, 'colsample_bytree': 0.8062881628748425}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:04:46,192] Trial 402 finished with value: 0.836 and parameters: {'learning_rate': 0.008613756857048278, 'n_estimators': 2205, 'max_depth': 18, 'subsample': 0.3935084235922344, 'colsample_bytree': 0.8259448274896198}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:04:56,871] Trial 403 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.010877449122918534, 'n_estimators': 2286, 'max_depth': 17, 'subsample': 0.43883959520884985, 'colsample_bytree': 0.8007412821902392}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:05:05,158] Trial 404 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.008210617401401027, 'n_estimators': 2399, 'max_depth': 44, 'subsample': 0.4127455641609195, 'colsample_bytree': 0.8538040913503098}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:05:15,790] Trial 405 finished with value: 0.842 and parameters: {'learning_rate': 0.007021128422052368, 'n_estimators': 2159, 'max_depth': 18, 'subsample': 0.43025834546876446, 'colsample_bytree': 0.7467731771553586}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:05:24,809] Trial 406 finished with value: 0.842 and parameters: {'learning_rate': 0.005913318334138832, 'n_estimators': 2226, 'max_depth': 21, 'subsample': 0.4482959589417512, 'colsample_bytree': 0.709955945153577}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:05:35,119] Trial 407 finished with value: 0.826 and parameters: {'learning_rate': 0.0012937354205296498, 'n_estimators': 2133, 'max_depth': 42, 'subsample': 0.5101409090650477, 'colsample_bytree': 0.6274614528562364}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:05:45,656] Trial 408 finished with value: 0.842 and parameters: {'learning_rate': 0.007469198568345767, 'n_estimators': 2193, 'max_depth': 19, 'subsample': 0.4875962455014324, 'colsample_bytree': 0.6647878059616217}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:05:56,269] Trial 409 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.000581666622118609, 'n_estimators': 2101, 'max_depth': 10, 'subsample': 0.630195811215146, 'colsample_bytree': 0.7299445170912784}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:06:06,989] Trial 410 finished with value: 0.836 and parameters: {'learning_rate': 0.009126916140234899, 'n_estimators': 2355, 'max_depth': 37, 'subsample': 0.44590505500190597, 'colsample_bytree': 0.6859799434620847}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:06:10,753] Trial 411 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.030550467786780274, 'n_estimators': 2231, 'max_depth': 9, 'subsample': 0.15870420316888734, 'colsample_bytree': 0.5879168234668438}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:06:23,359] Trial 412 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.005239919981412458, 'n_estimators': 2165, 'max_depth': 17, 'subsample': 0.533808560668759, 'colsample_bytree': 0.764778850343277}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:06:28,742] Trial 413 finished with value: 0.8300000000000001 and parameters: {'learning_rate': 0.022249065809516477, 'n_estimators': 2297, 'max_depth': 8, 'subsample': 0.3817308443891385, 'colsample_bytree': 0.5567855789707907}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:06:40,168] Trial 414 finished with value: 0.834 and parameters: {'learning_rate': 0.0020702706465230074, 'n_estimators': 1969, 'max_depth': 27, 'subsample': 0.4661267993410542, 'colsample_bytree': 0.7457386043678916}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:06:44,587] Trial 415 finished with value: 0.8219999999999998 and parameters: {'learning_rate': 0.047690960646447324, 'n_estimators': 1766, 'max_depth': 45, 'subsample': 0.4293895556229215, 'colsample_bytree': 0.7188642182816528}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:06:55,987] Trial 416 finished with value: 0.8280000000000001 and parameters: {'learning_rate': 0.0016987857248603022, 'n_estimators': 2087, 'max_depth': 48, 'subsample': 0.4083197051533777, 'colsample_bytree': 0.8126606670459257}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:07:09,229] Trial 417 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.0008470513938642264, 'n_estimators': 2700, 'max_depth': 41, 'subsample': 0.459073594384485, 'colsample_bytree': 0.6987121666070056}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:07:21,131] Trial 418 finished with value: 0.828 and parameters: {'learning_rate': 0.0010207367644881778, 'n_estimators': 2156, 'max_depth': 34, 'subsample': 0.5028999804574852, 'colsample_bytree': 0.9658478004014899}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:07:30,037] Trial 419 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.006903542186055637, 'n_estimators': 2229, 'max_depth': 20, 'subsample': 0.4795602749100448, 'colsample_bytree': 0.5068643234304766}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:07:34,320] Trial 420 finished with value: 0.76 and parameters: {'learning_rate': 0.010771260204481553, 'n_estimators': 2052, 'max_depth': 39, 'subsample': 0.7785741439134782, 'colsample_bytree': 0.11171549510769369}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:07:45,470] Trial 421 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.005744237722704082, 'n_estimators': 2123, 'max_depth': 17, 'subsample': 0.44251391719124294, 'colsample_bytree': 0.770245932668689}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:07:59,705] Trial 422 finished with value: 0.812 and parameters: {'learning_rate': 3.461075129626064e-05, 'n_estimators': 2472, 'max_depth': 43, 'subsample': 0.6383042352838666, 'colsample_bytree': 0.7507013947928743}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:08:07,126] Trial 423 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.003967729287248628, 'n_estimators': 1926, 'max_depth': 23, 'subsample': 0.4199392194077335, 'colsample_bytree': 0.7920371357733321}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:08:16,923] Trial 424 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.015392640291369216, 'n_estimators': 2015, 'max_depth': 16, 'subsample': 0.4767212673020807, 'colsample_bytree': 0.733972995340981}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:08:23,491] Trial 425 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.013103649107804595, 'n_estimators': 2266, 'max_depth': 46, 'subsample': 0.45552718011926213, 'colsample_bytree': 0.6174980609725719}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:08:36,229] Trial 426 finished with value: 0.8299999999999998 and parameters: {'learning_rate': 0.008975067934928796, 'n_estimators': 2191, 'max_depth': 24, 'subsample': 0.9876120383971905, 'colsample_bytree': 0.5395911772079821}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:08:45,187] Trial 427 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.004971789377944855, 'n_estimators': 2090, 'max_depth': 11, 'subsample': 0.4306921102425597, 'colsample_bytree': 0.7160361718106121}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:08:55,737] Trial 428 finished with value: 0.834 and parameters: {'learning_rate': 0.002983483505142585, 'n_estimators': 2328, 'max_depth': 36, 'subsample': 0.40076959589530187, 'colsample_bytree': 0.851152618273425}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:09:03,614] Trial 429 finished with value: 0.836 and parameters: {'learning_rate': 0.006696817290295722, 'n_estimators': 2012, 'max_depth': 40, 'subsample': 0.32580191133244507, 'colsample_bytree': 0.6567393023253592}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:09:12,515] Trial 430 finished with value: 0.844 and parameters: {'learning_rate': 0.005944762487144834, 'n_estimators': 2150, 'max_depth': 50, 'subsample': 0.49149393653791534, 'colsample_bytree': 0.7601524534570911}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:09:21,635] Trial 431 finished with value: 0.8219999999999998 and parameters: {'learning_rate': 0.026198042090372284, 'n_estimators': 2089, 'max_depth': 44, 'subsample': 0.5253573571491141, 'colsample_bytree': 0.73474625836397}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:09:28,635] Trial 432 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.008120500246191199, 'n_estimators': 2191, 'max_depth': 29, 'subsample': 0.4641465889615273, 'colsample_bytree': 0.6002237679422643}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:09:44,117] Trial 433 finished with value: 0.8360000000000001 and parameters: {'learning_rate': 0.004987208428229396, 'n_estimators': 2803, 'max_depth': 19, 'subsample': 0.6724980342608707, 'colsample_bytree': 0.6745411270207984}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:10:00,691] Trial 434 finished with value: 0.836 and parameters: {'learning_rate': 0.003524511487633181, 'n_estimators': 2251, 'max_depth': 38, 'subsample': 0.8112203994086953, 'colsample_bytree': 0.7773087000387421}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:10:06,153] Trial 435 finished with value: 0.8300000000000001 and parameters: {'learning_rate': 0.006985158922918163, 'n_estimators': 1992, 'max_depth': 32, 'subsample': 0.24840964257792264, 'colsample_bytree': 0.7068325725551838}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:10:14,087] Trial 436 finished with value: 0.826 and parameters: {'learning_rate': 0.09033176161185569, 'n_estimators': 2138, 'max_depth': 11, 'subsample': 0.9226718021538411, 'colsample_bytree': 0.8027247316358577}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:10:24,118] Trial 437 finished with value: 0.8459999999999999 and parameters: {'learning_rate': 0.004277934294274785, 'n_estimators': 2388, 'max_depth': 18, 'subsample': 0.44883952264993865, 'colsample_bytree': 0.7463875756264793}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:10:32,246] Trial 438 finished with value: 0.8280000000000001 and parameters: {'learning_rate': 0.017459973714438068, 'n_estimators': 1841, 'max_depth': 13, 'subsample': 0.7382190779574708, 'colsample_bytree': 0.6387322304727364}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:10:41,358] Trial 439 finished with value: 0.834 and parameters: {'learning_rate': 0.010230218677518882, 'n_estimators': 2060, 'max_depth': 41, 'subsample': 0.4752093624128619, 'colsample_bytree': 0.8326697207620836}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:10:51,162] Trial 440 finished with value: 0.842 and parameters: {'learning_rate': 0.005815449113161854, 'n_estimators': 2283, 'max_depth': 43, 'subsample': 0.5020877013908505, 'colsample_bytree': 0.6919837098599351}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:11:02,649] Trial 441 finished with value: 0.834 and parameters: {'learning_rate': 0.0025421482941491674, 'n_estimators': 2200, 'max_depth': 16, 'subsample': 0.42813940150797836, 'colsample_bytree': 0.7281000496183199}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:11:08,525] Trial 442 finished with value: 0.8460000000000001 and parameters: {'learning_rate': 0.007994232052352598, 'n_estimators': 1909, 'max_depth': 47, 'subsample': 0.4466400745311841, 'colsample_bytree': 0.5728110892682662}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:11:13,963] Trial 443 finished with value: 0.818 and parameters: {'learning_rate': 0.06398756086889669, 'n_estimators': 1909, 'max_depth': 47, 'subsample': 0.41149352744362433, 'colsample_bytree': 0.5744084312689163}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:11:21,620] Trial 444 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.008426805958608532, 'n_estimators': 1955, 'max_depth': 48, 'subsample': 0.4422333163401704, 'colsample_bytree': 0.5969632144699312}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:11:27,108] Trial 445 finished with value: 0.834 and parameters: {'learning_rate': 0.011560988181201408, 'n_estimators': 1860, 'max_depth': 10, 'subsample': 0.4499292567782788, 'colsample_bytree': 0.5481081333555002}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:11:35,695] Trial 446 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.007224450288480235, 'n_estimators': 1977, 'max_depth': 45, 'subsample': 0.37965119714875606, 'colsample_bytree': 0.5633843680026993}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:11:45,141] Trial 447 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.0012645441517953493, 'n_estimators': 2142, 'max_depth': 43, 'subsample': 0.4261300226225643, 'colsample_bytree': 0.7778962093024917}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:11:55,232] Trial 448 finished with value: 0.8140000000000001 and parameters: {'learning_rate': 0.0004847554045464934, 'n_estimators': 2333, 'max_depth': 7, 'subsample': 0.4579727053292769, 'colsample_bytree': 0.576391305690128}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:12:04,885] Trial 449 finished with value: 0.818 and parameters: {'learning_rate': 0.000923566534463829, 'n_estimators': 2209, 'max_depth': 50, 'subsample': 0.397319679024827, 'colsample_bytree': 0.6319513463431363}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:12:12,161] Trial 450 finished with value: 0.836 and parameters: {'learning_rate': 0.008727568923401353, 'n_estimators': 2102, 'max_depth': 46, 'subsample': 0.486530821663391, 'colsample_bytree': 0.5311051450945322}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:12:22,975] Trial 451 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.006254458892888378, 'n_estimators': 1795, 'max_depth': 26, 'subsample': 0.594747583072473, 'colsample_bytree': 0.7150108539631194}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:12:28,826] Trial 452 finished with value: 0.836 and parameters: {'learning_rate': 0.007569832364726337, 'n_estimators': 1907, 'max_depth': 35, 'subsample': 0.4372733632334733, 'colsample_bytree': 0.586677561559187}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:12:36,756] Trial 453 finished with value: 0.828 and parameters: {'learning_rate': 0.013601583401525733, 'n_estimators': 2024, 'max_depth': 40, 'subsample': 0.46762248661754735, 'colsample_bytree': 0.6143270010874884}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:12:42,727] Trial 454 finished with value: 0.8280000000000001 and parameters: {'learning_rate': 0.0101287366447008, 'n_estimators': 2263, 'max_depth': 37, 'subsample': 0.4204863594444447, 'colsample_bytree': 0.2526365804641553}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:12:47,993] Trial 455 finished with value: 0.828 and parameters: {'learning_rate': 0.03701582458550421, 'n_estimators': 2161, 'max_depth': 14, 'subsample': 0.3475738547713975, 'colsample_bytree': 0.8772246840629379}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:12:57,259] Trial 456 finished with value: 0.844 and parameters: {'learning_rate': 0.005194861899775879, 'n_estimators': 2102, 'max_depth': 21, 'subsample': 0.44589641046638884, 'colsample_bytree': 0.4370415757677182}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:13:01,283] Trial 457 finished with value: 0.818 and parameters: {'learning_rate': 0.0017940205212437965, 'n_estimators': 906, 'max_depth': 43, 'subsample': 0.5138645731870319, 'colsample_bytree': 0.7593087503318309}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:13:10,409] Trial 458 finished with value: 0.844 and parameters: {'learning_rate': 0.006056293284128143, 'n_estimators': 2051, 'max_depth': 6, 'subsample': 0.48436462990260215, 'colsample_bytree': 0.6970309538786365}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:13:18,495] Trial 459 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.0038950370172478816, 'n_estimators': 2222, 'max_depth': 5, 'subsample': 0.45722494416971504, 'colsample_bytree': 0.6535744569162426}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:13:29,517] Trial 460 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.007417783980284217, 'n_estimators': 2290, 'max_depth': 33, 'subsample': 0.433739530448148, 'colsample_bytree': 0.8107849094612428}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:13:37,249] Trial 461 finished with value: 0.842 and parameters: {'learning_rate': 0.004614133828452468, 'n_estimators': 1959, 'max_depth': 48, 'subsample': 0.4687850368265838, 'colsample_bytree': 0.7341203111175894}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:13:41,617] Trial 462 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.020677964233687066, 'n_estimators': 2157, 'max_depth': 41, 'subsample': 0.10152427360192995, 'colsample_bytree': 0.5231265216405462}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:13:46,899] Trial 463 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.009564623758280402, 'n_estimators': 2013, 'max_depth': 15, 'subsample': 0.13461192571827602, 'colsample_bytree': 0.7915006547828357}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:13:52,310] Trial 464 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.052741050656421526, 'n_estimators': 2102, 'max_depth': 12, 'subsample': 0.5379214159840243, 'colsample_bytree': 0.7611986863255966}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:14:02,156] Trial 465 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.006369887471985523, 'n_estimators': 2357, 'max_depth': 14, 'subsample': 0.40765000895239084, 'colsample_bytree': 0.5467721455567458}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:14:10,403] Trial 466 finished with value: 0.844 and parameters: {'learning_rate': 0.0053453268160349385, 'n_estimators': 2214, 'max_depth': 39, 'subsample': 0.49170671608862965, 'colsample_bytree': 0.682441592077336}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:14:23,199] Trial 467 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.003281036249969511, 'n_estimators': 2553, 'max_depth': 42, 'subsample': 0.4437835334748331, 'colsample_bytree': 0.7175145604158111}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:14:35,299] Trial 468 finished with value: 0.8140000000000001 and parameters: {'learning_rate': 0.00012845917053310992, 'n_estimators': 2051, 'max_depth': 22, 'subsample': 0.6075335959417237, 'colsample_bytree': 0.7412378182435728}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:14:42,375] Trial 469 finished with value: 0.8380000000000001 and parameters: {'learning_rate': 0.007937082546674305, 'n_estimators': 2149, 'max_depth': 45, 'subsample': 0.4670934282780196, 'colsample_bytree': 0.6033547832122135}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:14:53,136] Trial 470 finished with value: 0.8160000000000001 and parameters: {'learning_rate': 0.0008092985876768013, 'n_estimators': 2255, 'max_depth': 30, 'subsample': 0.4270177442038465, 'colsample_bytree': 0.562067530436796}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:15:01,594] Trial 471 finished with value: 0.818 and parameters: {'learning_rate': 0.00035175566101382135, 'n_estimators': 1929, 'max_depth': 27, 'subsample': 0.5030106773998142, 'colsample_bytree': 0.7664993204025404}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:15:12,818] Trial 472 finished with value: 0.8320000000000001 and parameters: {'learning_rate': 0.012305616353756373, 'n_estimators': 2105, 'max_depth': 13, 'subsample': 0.6949742380505869, 'colsample_bytree': 0.7026680031653526}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:15:22,352] Trial 473 finished with value: 0.844 and parameters: {'learning_rate': 0.006594571090941592, 'n_estimators': 2191, 'max_depth': 38, 'subsample': 0.4531602589638955, 'colsample_bytree': 0.7298762226484039}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:15:31,753] Trial 474 finished with value: 0.842 and parameters: {'learning_rate': 0.00441856212473649, 'n_estimators': 2016, 'max_depth': 35, 'subsample': 0.4778054262122098, 'colsample_bytree': 0.7814347403976711}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:15:32,427] Trial 475 finished with value: 0.808 and parameters: {'learning_rate': 0.005422398730125766, 'n_estimators': 147, 'max_depth': 45, 'subsample': 0.42212006952555503, 'colsample_bytree': 0.6244862588005003}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:15:39,689] Trial 476 finished with value: 0.834 and parameters: {'learning_rate': 0.00926156892646453, 'n_estimators': 2301, 'max_depth': 48, 'subsample': 0.2110177227449871, 'colsample_bytree': 0.7502899993266491}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:15:49,466] Trial 477 finished with value: 0.844 and parameters: {'learning_rate': 0.003894264104998383, 'n_estimators': 2080, 'max_depth': 25, 'subsample': 0.441569337665939, 'colsample_bytree': 0.9797073748513272}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:15:58,627] Trial 478 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.016954045438980034, 'n_estimators': 2461, 'max_depth': 40, 'subsample': 0.39750435767522035, 'colsample_bytree': 0.5837506479990037}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:16:04,288] Trial 479 finished with value: 0.8240000000000001 and parameters: {'learning_rate': 0.006939478384775237, 'n_estimators': 2180, 'max_depth': 15, 'subsample': 0.5698100908680453, 'colsample_bytree': 0.28829411788548776}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:16:13,306] Trial 480 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.0050000915505421595, 'n_estimators': 2115, 'max_depth': 8, 'subsample': 0.4591150285865352, 'colsample_bytree': 0.4891503773577483}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:16:23,240] Trial 481 finished with value: 0.8319999999999999 and parameters: {'learning_rate': 0.008090442317208213, 'n_estimators': 2250, 'max_depth': 9, 'subsample': 0.7502258641153144, 'colsample_bytree': 0.6679949778056337}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:16:33,102] Trial 482 finished with value: 0.82 and parameters: {'learning_rate': 0.0277236069775814, 'n_estimators': 2025, 'max_depth': 20, 'subsample': 0.6665852986521724, 'colsample_bytree': 0.822514597477841}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:16:41,678] Trial 483 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.0030850273314181253, 'n_estimators': 1956, 'max_depth': 17, 'subsample': 0.48295293148388413, 'colsample_bytree': 0.7204763407876273}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:16:49,071] Trial 484 finished with value: 0.8219999999999998 and parameters: {'learning_rate': 0.041802965686858304, 'n_estimators': 1888, 'max_depth': 22, 'subsample': 0.36929082323043994, 'colsample_bytree': 0.796823036869522}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:16:54,068] Trial 485 finished with value: 0.826 and parameters: {'learning_rate': 0.07791602377346303, 'n_estimators': 2408, 'max_depth': 16, 'subsample': 0.4401917283136207, 'colsample_bytree': 0.7496081424374464}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:17:06,282] Trial 486 finished with value: 0.836 and parameters: {'learning_rate': 0.0024136772985820336, 'n_estimators': 2158, 'max_depth': 19, 'subsample': 0.5126024622956267, 'colsample_bytree': 0.6821391338233274}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:17:18,887] Trial 487 finished with value: 0.8299999999999998 and parameters: {'learning_rate': 0.005846327059884492, 'n_estimators': 2216, 'max_depth': 43, 'subsample': 0.8374804632897327, 'colsample_bytree': 0.6454805317587567}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:17:21,203] Trial 488 finished with value: 0.8300000000000001 and parameters: {'learning_rate': 0.010429121141680544, 'n_estimators': 406, 'max_depth': 29, 'subsample': 0.4104123002671493, 'colsample_bytree': 0.7744765966896833}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:17:30,000] Trial 489 finished with value: 0.842 and parameters: {'learning_rate': 0.0042467493310605915, 'n_estimators': 2077, 'max_depth': 24, 'subsample': 0.4689966708713133, 'colsample_bytree': 0.8659734753677665}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:17:42,024] Trial 490 finished with value: 0.818 and parameters: {'learning_rate': 2.107253931428329e-05, 'n_estimators': 2353, 'max_depth': 31, 'subsample': 0.4935146339311732, 'colsample_bytree': 0.705099452125966}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:17:51,523] Trial 491 finished with value: 0.844 and parameters: {'learning_rate': 0.0064802319162571695, 'n_estimators': 2137, 'max_depth': 41, 'subsample': 0.4588313447171988, 'colsample_bytree': 0.7252822893115555}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:17:59,054] Trial 492 finished with value: 0.8400000000000001 and parameters: {'learning_rate': 0.005020625554684167, 'n_estimators': 1982, 'max_depth': 46, 'subsample': 0.4265232454419557, 'colsample_bytree': 0.6107574289408209}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:18:10,487] Trial 493 finished with value: 0.834 and parameters: {'learning_rate': 0.00815985278446881, 'n_estimators': 2278, 'max_depth': 28, 'subsample': 0.5271681328112517, 'colsample_bytree': 0.7417675788209983}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:18:26,295] Trial 494 finished with value: 0.8379999999999999 and parameters: {'learning_rate': 0.003496771002813272, 'n_estimators': 2618, 'max_depth': 37, 'subsample': 0.6504319952442539, 'colsample_bytree': 0.7673008375326494}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:18:27,923] Trial 495 finished with value: 0.798 and parameters: {'learning_rate': 0.002041287989161599, 'n_estimators': 539, 'max_depth': 12, 'subsample': 0.2801804632391856, 'colsample_bytree': 0.6961493585932694}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:18:34,073] Trial 496 finished with value: 0.828 and parameters: {'learning_rate': 0.012272530906278414, 'n_estimators': 2067, 'max_depth': 14, 'subsample': 0.47844295697394995, 'colsample_bytree': 0.5722172383850017}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:18:43,556] Trial 497 finished with value: 0.844 and parameters: {'learning_rate': 0.005866500861863711, 'n_estimators': 1731, 'max_depth': 23, 'subsample': 0.4467248320232409, 'colsample_bytree': 0.7548376854783445}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:18:47,679] Trial 498 finished with value: 0.818 and parameters: {'learning_rate': 0.007244507852773506, 'n_estimators': 2198, 'max_depth': 44, 'subsample': 0.31175730648916167, 'colsample_bytree': 0.22251137906537993}. Best is trial 278 with value: 0.85.\n",
            "[I 2023-09-21 15:18:49,657] Trial 499 finished with value: 0.808 and parameters: {'learning_rate': 0.004248020379974202, 'n_estimators': 666, 'max_depth': 50, 'subsample': 0.4150894834259308, 'colsample_bytree': 0.35752401507660747}. Best is trial 278 with value: 0.85.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "XGB best parameters:  {'learning_rate': 0.0052493969604778335, 'n_estimators': 2063, 'max_depth': 17, 'subsample': 0.4686499286014045, 'colsample_bytree': 0.7475032992018813}\n"
          ]
        }
      ],
      "source": [
        "run_optimization('xgb', Afghanistan_train_data, 500)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JGcaZUfVurqs",
        "outputId": "cb8c5dc9-2554-4572-c385-3b12e420505b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[I 2023-09-21 15:18:49,683] A new study created in memory with name: no-name-66199ba4-22d5-4318-963a-e101303d3797\n",
            "[I 2023-09-21 15:19:25,318] Trial 0 finished with value: 0.938 and parameters: {'learning_rate': 5.892402514188225e-05, 'n_estimators': 2992, 'max_depth': 31, 'subsample': 0.3722323052831178, 'colsample_bytree': 0.5751058942959152}. Best is trial 0 with value: 0.938.\n",
            "[I 2023-09-21 15:20:18,699] Trial 1 finished with value: 0.942 and parameters: {'learning_rate': 0.00015006991755663925, 'n_estimators': 2452, 'max_depth': 14, 'subsample': 0.8350158549603934, 'colsample_bytree': 0.46549025105601083}. Best is trial 1 with value: 0.942.\n",
            "[I 2023-09-21 15:20:22,857] Trial 2 finished with value: 0.942 and parameters: {'learning_rate': 0.0002023283640316383, 'n_estimators': 96, 'max_depth': 16, 'subsample': 0.8765828014113869, 'colsample_bytree': 0.7166071816337113}. Best is trial 1 with value: 0.942.\n",
            "[I 2023-09-21 15:20:36,685] Trial 3 finished with value: 0.9400000000000001 and parameters: {'learning_rate': 2.2620603443497577e-05, 'n_estimators': 474, 'max_depth': 29, 'subsample': 0.6692468667151403, 'colsample_bytree': 0.9493493113699943}. Best is trial 1 with value: 0.942.\n",
            "[I 2023-09-21 15:21:54,386] Trial 4 finished with value: 0.924 and parameters: {'learning_rate': 0.00013673691831179375, 'n_estimators': 1865, 'max_depth': 46, 'subsample': 0.9828421782953471, 'colsample_bytree': 0.8816653923365478}. Best is trial 1 with value: 0.942.\n",
            "[I 2023-09-21 15:22:55,612] Trial 5 finished with value: 0.9400000000000001 and parameters: {'learning_rate': 3.886356220133581e-05, 'n_estimators': 1986, 'max_depth': 30, 'subsample': 0.995474298329983, 'colsample_bytree': 0.6459079248832286}. Best is trial 1 with value: 0.942.\n",
            "[I 2023-09-21 15:22:58,298] Trial 6 finished with value: 0.958 and parameters: {'learning_rate': 0.07841695583315184, 'n_estimators': 923, 'max_depth': 10, 'subsample': 0.13945660774886054, 'colsample_bytree': 0.31351145367196886}. Best is trial 6 with value: 0.958.\n",
            "[I 2023-09-21 15:23:22,308] Trial 7 finished with value: 0.9400000000000001 and parameters: {'learning_rate': 1.3417761124197426e-05, 'n_estimators': 2064, 'max_depth': 5, 'subsample': 0.4603965584716655, 'colsample_bytree': 0.40842612004256673}. Best is trial 6 with value: 0.958.\n",
            "[I 2023-09-21 15:23:46,850] Trial 8 finished with value: 0.958 and parameters: {'learning_rate': 0.011712864601684797, 'n_estimators': 2924, 'max_depth': 8, 'subsample': 0.4711552038648408, 'colsample_bytree': 0.658883848446961}. Best is trial 6 with value: 0.958.\n",
            "[I 2023-09-21 15:23:50,068] Trial 9 finished with value: 0.932 and parameters: {'learning_rate': 0.0008816895768515913, 'n_estimators': 785, 'max_depth': 23, 'subsample': 0.15756271134584265, 'colsample_bytree': 0.27639923147569356}. Best is trial 6 with value: 0.958.\n",
            "[I 2023-09-21 15:23:54,625] Trial 10 finished with value: 0.96 and parameters: {'learning_rate': 0.0852537446878629, 'n_estimators': 1161, 'max_depth': 9, 'subsample': 0.15498025519187208, 'colsample_bytree': 0.11411094896447066}. Best is trial 10 with value: 0.96.\n",
            "[I 2023-09-21 15:23:59,294] Trial 11 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.09554033978735053, 'n_estimators': 1182, 'max_depth': 10, 'subsample': 0.11199173749264167, 'colsample_bytree': 0.11563889079423281}. Best is trial 10 with value: 0.96.\n",
            "[I 2023-09-21 15:24:02,791] Trial 12 finished with value: 0.958 and parameters: {'learning_rate': 0.0843575080802739, 'n_estimators': 1228, 'max_depth': 8, 'subsample': 0.2612425297633585, 'colsample_bytree': 0.1338322591404071}. Best is trial 10 with value: 0.96.\n",
            "[I 2023-09-21 15:24:06,187] Trial 13 finished with value: 0.962 and parameters: {'learning_rate': 0.017444554018695674, 'n_estimators': 863, 'max_depth': 5, 'subsample': 0.26355662775996525, 'colsample_bytree': 0.25536387139980476}. Best is trial 13 with value: 0.962.\n",
            "[I 2023-09-21 15:24:14,913] Trial 14 finished with value: 0.962 and parameters: {'learning_rate': 0.015200802326837196, 'n_estimators': 1624, 'max_depth': 5, 'subsample': 0.22671452004345183, 'colsample_bytree': 0.25160681191762135}. Best is trial 13 with value: 0.962.\n",
            "[I 2023-09-21 15:24:21,881] Trial 15 finished with value: 0.958 and parameters: {'learning_rate': 0.00785808688640123, 'n_estimators': 1623, 'max_depth': 5, 'subsample': 0.29235531856679525, 'colsample_bytree': 0.26998272702738363}. Best is trial 13 with value: 0.962.\n",
            "[I 2023-09-21 15:24:26,389] Trial 16 finished with value: 0.958 and parameters: {'learning_rate': 0.008262663327022513, 'n_estimators': 580, 'max_depth': 6, 'subsample': 0.2868919883734401, 'colsample_bytree': 0.41906618549711094}. Best is trial 13 with value: 0.962.\n",
            "[I 2023-09-21 15:24:36,188] Trial 17 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.020338994934076055, 'n_estimators': 1511, 'max_depth': 6, 'subsample': 0.6000952242129366, 'colsample_bytree': 0.2562360361246786}. Best is trial 17 with value: 0.9620000000000001.\n",
            "[I 2023-09-21 15:24:37,820] Trial 18 finished with value: 0.95 and parameters: {'learning_rate': 0.0026386736246644866, 'n_estimators': 209, 'max_depth': 7, 'subsample': 0.5803044295419254, 'colsample_bytree': 0.19471317514048556}. Best is trial 17 with value: 0.9620000000000001.\n",
            "[I 2023-09-21 15:24:52,546] Trial 19 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.023930247612725906, 'n_estimators': 2328, 'max_depth': 6, 'subsample': 0.6504496260867461, 'colsample_bytree': 0.3638522596468651}. Best is trial 17 with value: 0.9620000000000001.\n",
            "[I 2023-09-21 15:25:03,187] Trial 20 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.002672956230295752, 'n_estimators': 1519, 'max_depth': 6, 'subsample': 0.38061129862726006, 'colsample_bytree': 0.20974295672679522}. Best is trial 17 with value: 0.9620000000000001.\n",
            "[I 2023-09-21 15:25:09,182] Trial 21 finished with value: 0.9559999999999998 and parameters: {'learning_rate': 0.026621410490601065, 'n_estimators': 1617, 'max_depth': 5, 'subsample': 0.2271588382630948, 'colsample_bytree': 0.3241965460102856}. Best is trial 17 with value: 0.9620000000000001.\n",
            "[I 2023-09-21 15:25:14,803] Trial 22 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.027724563403121356, 'n_estimators': 1403, 'max_depth': 5, 'subsample': 0.3887795579701041, 'colsample_bytree': 0.21820909369631422}. Best is trial 17 with value: 0.9620000000000001.\n",
            "[I 2023-09-21 15:25:22,833] Trial 23 finished with value: 0.952 and parameters: {'learning_rate': 0.030372294883921205, 'n_estimators': 1362, 'max_depth': 7, 'subsample': 0.36793508610116044, 'colsample_bytree': 0.20073217978444344}. Best is trial 17 with value: 0.9620000000000001.\n",
            "[I 2023-09-21 15:25:27,920] Trial 24 finished with value: 0.958 and parameters: {'learning_rate': 0.0407790021168474, 'n_estimators': 1010, 'max_depth': 5, 'subsample': 0.498744053607339, 'colsample_bytree': 0.3647568230772412}. Best is trial 17 with value: 0.9620000000000001.\n",
            "[I 2023-09-21 15:25:39,135] Trial 25 finished with value: 0.954 and parameters: {'learning_rate': 0.005428645494341523, 'n_estimators': 622, 'max_depth': 6, 'subsample': 0.5639383100483658, 'colsample_bytree': 0.49047778368996253}. Best is trial 17 with value: 0.9620000000000001.\n",
            "[I 2023-09-21 15:25:44,741] Trial 26 finished with value: 0.9580000000000002 and parameters: {'learning_rate': 0.018362694916032048, 'n_estimators': 1394, 'max_depth': 13, 'subsample': 0.4264101006455995, 'colsample_bytree': 0.1852471251263948}. Best is trial 17 with value: 0.9620000000000001.\n",
            "[I 2023-09-21 15:25:52,196] Trial 27 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.005832614842478902, 'n_estimators': 866, 'max_depth': 7, 'subsample': 0.3700304864896907, 'colsample_bytree': 0.26812548101626904}. Best is trial 17 with value: 0.9620000000000001.\n",
            "[I 2023-09-21 15:26:00,225] Trial 28 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.05151308617693283, 'n_estimators': 1777, 'max_depth': 11, 'subsample': 0.5250969587296586, 'colsample_bytree': 0.36458454915253347}. Best is trial 17 with value: 0.9620000000000001.\n",
            "[I 2023-09-21 15:26:01,915] Trial 29 finished with value: 0.968 and parameters: {'learning_rate': 0.04074652544112853, 'n_estimators': 454, 'max_depth': 8, 'subsample': 0.3153099125619524, 'colsample_bytree': 0.1593272485470127}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:26:03,571] Trial 30 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.039312751727359284, 'n_estimators': 347, 'max_depth': 8, 'subsample': 0.41910056217122216, 'colsample_bytree': 0.16685257822629002}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:26:10,322] Trial 31 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.01536637053018155, 'n_estimators': 1069, 'max_depth': 6, 'subsample': 0.3261671806561187, 'colsample_bytree': 0.10102482365708396}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:26:12,996] Trial 32 finished with value: 0.96 and parameters: {'learning_rate': 0.04742180650171408, 'n_estimators': 716, 'max_depth': 5, 'subsample': 0.3301909852964269, 'colsample_bytree': 0.22513139133925641}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:26:14,154] Trial 33 finished with value: 0.9579999999999999 and parameters: {'learning_rate': 0.024147758872038547, 'n_estimators': 280, 'max_depth': 6, 'subsample': 0.22906377006395368, 'colsample_bytree': 0.15999492568303691}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:26:14,791] Trial 34 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.05261434642962756, 'n_estimators': 81, 'max_depth': 7, 'subsample': 0.43652216983856057, 'colsample_bytree': 0.21937765150029362}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:26:18,867] Trial 35 finished with value: 0.9579999999999999 and parameters: {'learning_rate': 0.012292785811275495, 'n_estimators': 448, 'max_depth': 18, 'subsample': 0.6219113524486078, 'colsample_bytree': 0.3068592963803959}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:26:27,958] Trial 36 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.027136044355974748, 'n_estimators': 1404, 'max_depth': 11, 'subsample': 0.7421446496247094, 'colsample_bytree': 0.1555827492424684}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:26:36,874] Trial 37 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.027357605229811656, 'n_estimators': 2548, 'max_depth': 12, 'subsample': 0.7156238336922967, 'colsample_bytree': 0.141620280645083}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:26:46,853] Trial 38 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.05487900249258788, 'n_estimators': 2035, 'max_depth': 15, 'subsample': 0.7450829756690036, 'colsample_bytree': 0.18010794211733894}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:26:53,694] Trial 39 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.034008347715307516, 'n_estimators': 1878, 'max_depth': 9, 'subsample': 0.5226884022896918, 'colsample_bytree': 0.1531511606632367}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:27:02,476] Trial 40 finished with value: 0.962 and parameters: {'learning_rate': 0.010473124637758856, 'n_estimators': 1350, 'max_depth': 11, 'subsample': 0.8196265646064649, 'colsample_bytree': 0.10271584893727974}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:27:12,865] Trial 41 finished with value: 0.966 and parameters: {'learning_rate': 0.0266468047214752, 'n_estimators': 2610, 'max_depth': 12, 'subsample': 0.729094745751524, 'colsample_bytree': 0.14878830802247367}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:27:23,567] Trial 42 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.062418073566220034, 'n_estimators': 2880, 'max_depth': 13, 'subsample': 0.7028432771232529, 'colsample_bytree': 0.22622660572955697}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:27:33,055] Trial 43 finished with value: 0.958 and parameters: {'learning_rate': 0.09926355649577154, 'n_estimators': 2162, 'max_depth': 17, 'subsample': 0.6128051995627065, 'colsample_bytree': 0.1574448128011606}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:27:44,579] Trial 44 finished with value: 0.96 and parameters: {'learning_rate': 0.03621279752424391, 'n_estimators': 2607, 'max_depth': 10, 'subsample': 0.7794854020005199, 'colsample_bytree': 0.30824968246437345}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:27:52,935] Trial 45 finished with value: 0.958 and parameters: {'learning_rate': 0.020116086471101066, 'n_estimators': 1787, 'max_depth': 9, 'subsample': 0.6426958700723809, 'colsample_bytree': 0.10003676267185597}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:28:01,040] Trial 46 finished with value: 0.9579999999999999 and parameters: {'learning_rate': 0.06930667049013159, 'n_estimators': 2321, 'max_depth': 48, 'subsample': 0.8922573887459573, 'colsample_bytree': 0.1455707341485098}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:28:10,609] Trial 47 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.01790257607548298, 'n_estimators': 1499, 'max_depth': 14, 'subsample': 0.6771785852132362, 'colsample_bytree': 0.24323918674606626}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:28:17,502] Trial 48 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.036562962118933506, 'n_estimators': 1283, 'max_depth': 8, 'subsample': 0.5734906562688553, 'colsample_bytree': 0.2847809180876276}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:28:30,042] Trial 49 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.013356668497394114, 'n_estimators': 2780, 'max_depth': 36, 'subsample': 0.4776000518224077, 'colsample_bytree': 0.19642513477239093}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:28:37,702] Trial 50 finished with value: 0.962 and parameters: {'learning_rate': 0.05754116890043947, 'n_estimators': 1157, 'max_depth': 11, 'subsample': 0.6842552069783128, 'colsample_bytree': 0.25641738921709817}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:28:46,675] Trial 51 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.025645507828905286, 'n_estimators': 2588, 'max_depth': 12, 'subsample': 0.7336069737682079, 'colsample_bytree': 0.13960613792283172}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:28:57,716] Trial 52 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.024964243743534852, 'n_estimators': 2214, 'max_depth': 13, 'subsample': 0.7512007686995906, 'colsample_bytree': 0.13370230529878757}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:29:09,183] Trial 53 finished with value: 0.962 and parameters: {'learning_rate': 0.018617806051590056, 'n_estimators': 2724, 'max_depth': 12, 'subsample': 0.7446809266347292, 'colsample_bytree': 0.13369941724500597}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:29:20,785] Trial 54 finished with value: 0.96 and parameters: {'learning_rate': 0.009351415497738184, 'n_estimators': 2409, 'max_depth': 15, 'subsample': 0.7946206266235193, 'colsample_bytree': 0.13662280866695448}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:29:30,851] Trial 55 finished with value: 0.9540000000000001 and parameters: {'learning_rate': 0.07623197064932268, 'n_estimators': 2188, 'max_depth': 10, 'subsample': 0.7348444309015678, 'colsample_bytree': 0.18285731540651032}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:29:41,041] Trial 56 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.024799618326579027, 'n_estimators': 2595, 'max_depth': 14, 'subsample': 0.8617901416970116, 'colsample_bytree': 0.1236581263865226}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:29:49,996] Trial 57 finished with value: 0.954 and parameters: {'learning_rate': 0.09941220607307445, 'n_estimators': 2576, 'max_depth': 19, 'subsample': 0.8692464566800708, 'colsample_bytree': 0.1295836703348629}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:30:04,059] Trial 58 finished with value: 0.958 and parameters: {'learning_rate': 0.026638803404056118, 'n_estimators': 2964, 'max_depth': 16, 'subsample': 0.7789362472492136, 'colsample_bytree': 0.1749710002982769}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:30:17,035] Trial 59 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.01362950341749172, 'n_estimators': 2726, 'max_depth': 14, 'subsample': 0.8440413663990575, 'colsample_bytree': 0.12128390749109258}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:30:26,241] Trial 60 finished with value: 0.952 and parameters: {'learning_rate': 0.045126043792788645, 'n_estimators': 2427, 'max_depth': 12, 'subsample': 0.9247735625964912, 'colsample_bytree': 0.2305771065403739}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:30:40,002] Trial 61 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.012636001217835898, 'n_estimators': 2694, 'max_depth': 14, 'subsample': 0.8566935715513775, 'colsample_bytree': 0.12085434541853254}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:30:53,478] Trial 62 finished with value: 0.958 and parameters: {'learning_rate': 0.03270958871992558, 'n_estimators': 2789, 'max_depth': 16, 'subsample': 0.8235530934379144, 'colsample_bytree': 0.19412120709586406}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:31:02,658] Trial 63 finished with value: 0.962 and parameters: {'learning_rate': 0.022473685002722902, 'n_estimators': 2242, 'max_depth': 11, 'subsample': 0.7732101154148352, 'colsample_bytree': 0.15770298931485285}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:31:16,629] Trial 64 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.007251897359192756, 'n_estimators': 2528, 'max_depth': 13, 'subsample': 0.8295428570437808, 'colsample_bytree': 0.1255542322911832}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:31:29,638] Trial 65 finished with value: 0.962 and parameters: {'learning_rate': 0.015341693736995994, 'n_estimators': 2661, 'max_depth': 13, 'subsample': 0.7064245061639794, 'colsample_bytree': 0.1054010720863387}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:31:39,985] Trial 66 finished with value: 0.96 and parameters: {'learning_rate': 0.07212900594248342, 'n_estimators': 2323, 'max_depth': 14, 'subsample': 0.8050228003572739, 'colsample_bytree': 0.2040338263085514}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:31:55,410] Trial 67 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.010790598494760977, 'n_estimators': 2884, 'max_depth': 10, 'subsample': 0.8537210910872604, 'colsample_bytree': 0.1704239323979448}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:32:05,403] Trial 68 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.042946411345597214, 'n_estimators': 2484, 'max_depth': 15, 'subsample': 0.9017120650926733, 'colsample_bytree': 0.2478035043810592}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:32:17,564] Trial 69 finished with value: 0.96 and parameters: {'learning_rate': 0.022718040712673512, 'n_estimators': 2117, 'max_depth': 20, 'subsample': 0.7578972309977612, 'colsample_bytree': 0.20941143236819257}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:32:29,436] Trial 70 finished with value: 0.96 and parameters: {'learning_rate': 0.03135740351549028, 'n_estimators': 2786, 'max_depth': 12, 'subsample': 0.8027281727355315, 'colsample_bytree': 0.1344381815405704}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:32:40,096] Trial 71 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.012992935071319971, 'n_estimators': 2671, 'max_depth': 14, 'subsample': 0.8600005444819507, 'colsample_bytree': 0.12412281373638887}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:32:54,984] Trial 72 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.016518291164875153, 'n_estimators': 2995, 'max_depth': 17, 'subsample': 0.8440464785349222, 'colsample_bytree': 0.16410089841653536}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:33:06,697] Trial 73 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.022525178027664294, 'n_estimators': 2397, 'max_depth': 14, 'subsample': 0.9405000835316892, 'colsample_bytree': 0.12141262779966051}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:33:18,248] Trial 74 finished with value: 0.96 and parameters: {'learning_rate': 0.04178030729090246, 'n_estimators': 2648, 'max_depth': 13, 'subsample': 0.7337878496710807, 'colsample_bytree': 0.18539538453615576}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:33:30,823] Trial 75 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.00769420630754365, 'n_estimators': 2833, 'max_depth': 12, 'subsample': 0.8414016351978687, 'colsample_bytree': 0.10236494218014686}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:33:41,698] Trial 76 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.012660328641562616, 'n_estimators': 1930, 'max_depth': 16, 'subsample': 0.7591265424498146, 'colsample_bytree': 0.151501159197382}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:33:54,587] Trial 77 finished with value: 0.954 and parameters: {'learning_rate': 0.029973801956567864, 'n_estimators': 2492, 'max_depth': 15, 'subsample': 0.6617808645621235, 'colsample_bytree': 0.23748110844193343}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:34:09,946] Trial 78 finished with value: 0.96 and parameters: {'learning_rate': 0.053995184554821635, 'n_estimators': 2737, 'max_depth': 11, 'subsample': 0.791634941001045, 'colsample_bytree': 0.2144840756452061}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:34:35,990] Trial 79 finished with value: 0.966 and parameters: {'learning_rate': 0.005789372787733306, 'n_estimators': 2687, 'max_depth': 9, 'subsample': 0.872495408342461, 'colsample_bytree': 0.17226324610425137}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:35:03,982] Trial 80 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.005744418994997412, 'n_estimators': 2558, 'max_depth': 9, 'subsample': 0.8777517216266632, 'colsample_bytree': 0.2806749971464628}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:35:17,944] Trial 81 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.01626311204092314, 'n_estimators': 2699, 'max_depth': 10, 'subsample': 0.969192300846508, 'colsample_bytree': 0.1486078416391511}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:35:31,517] Trial 82 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.010786356649378893, 'n_estimators': 2253, 'max_depth': 11, 'subsample': 0.8186333715847007, 'colsample_bytree': 0.17755678137216654}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:35:41,337] Trial 83 finished with value: 0.96 and parameters: {'learning_rate': 0.021402471239134167, 'n_estimators': 2898, 'max_depth': 14, 'subsample': 0.8776199352751084, 'colsample_bytree': 0.11948155643303082}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:35:54,033] Trial 84 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.02857391544507018, 'n_estimators': 2651, 'max_depth': 9, 'subsample': 0.8452463578876541, 'colsample_bytree': 0.16426422595482282}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:35:55,711] Trial 85 finished with value: 0.952 and parameters: {'learning_rate': 0.014661480075484758, 'n_estimators': 185, 'max_depth': 12, 'subsample': 0.7154890129365952, 'colsample_bytree': 0.1988197665651359}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:36:12,599] Trial 86 finished with value: 0.962 and parameters: {'learning_rate': 0.004089611274738063, 'n_estimators': 2827, 'max_depth': 13, 'subsample': 0.7675642904492251, 'colsample_bytree': 0.11917448974932636}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:36:26,355] Trial 87 finished with value: 0.962 and parameters: {'learning_rate': 0.009860559880397878, 'n_estimators': 2362, 'max_depth': 15, 'subsample': 0.8122988515157927, 'colsample_bytree': 0.1465577222383414}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:36:39,310] Trial 88 finished with value: 0.958 and parameters: {'learning_rate': 0.03586259135620206, 'n_estimators': 2597, 'max_depth': 17, 'subsample': 0.9023146734676918, 'colsample_bytree': 0.21841230138938184}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:36:46,721] Trial 89 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.018867050350685595, 'n_estimators': 1707, 'max_depth': 13, 'subsample': 0.6914174907084468, 'colsample_bytree': 0.1823441785732047}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:36:51,474] Trial 90 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.024769954853541054, 'n_estimators': 577, 'max_depth': 8, 'subsample': 0.7970388185611532, 'colsample_bytree': 0.1002964443769474}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:37:04,399] Trial 91 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.007037684992360911, 'n_estimators': 2505, 'max_depth': 13, 'subsample': 0.8294875549356278, 'colsample_bytree': 0.1306532720607551}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:37:18,029] Trial 92 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.009359201446112759, 'n_estimators': 2548, 'max_depth': 11, 'subsample': 0.8344320930903067, 'colsample_bytree': 0.12402254865778975}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:37:31,324] Trial 93 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.013320067041600861, 'n_estimators': 2464, 'max_depth': 12, 'subsample': 0.8592437590956421, 'colsample_bytree': 0.13919031304650892}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:37:41,741] Trial 94 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.04742814562395851, 'n_estimators': 2623, 'max_depth': 14, 'subsample': 0.7260261754327496, 'colsample_bytree': 0.16137009276742}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:37:49,338] Trial 95 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.0076068223454467, 'n_estimators': 1004, 'max_depth': 10, 'subsample': 0.7516414022964937, 'colsample_bytree': 0.18706469514667012}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:38:00,637] Trial 96 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.018661089178430276, 'n_estimators': 2264, 'max_depth': 14, 'subsample': 0.884075147438013, 'colsample_bytree': 0.1135006719091419}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:38:09,492] Trial 97 finished with value: 0.96 and parameters: {'learning_rate': 0.0644104532724942, 'n_estimators': 2933, 'max_depth': 13, 'subsample': 0.7816460137501884, 'colsample_bytree': 0.15027568039347727}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:38:23,417] Trial 98 finished with value: 0.96 and parameters: {'learning_rate': 0.0269067151488337, 'n_estimators': 2730, 'max_depth': 12, 'subsample': 0.7026591204303368, 'colsample_bytree': 0.20406805516020354}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:38:38,437] Trial 99 finished with value: 0.966 and parameters: {'learning_rate': 0.01158751970568805, 'n_estimators': 2521, 'max_depth': 15, 'subsample': 0.8137190675248607, 'colsample_bytree': 0.16721089038643522}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:38:51,781] Trial 100 finished with value: 0.96 and parameters: {'learning_rate': 0.03730167462898023, 'n_estimators': 2835, 'max_depth': 16, 'subsample': 0.7723387085556737, 'colsample_bytree': 0.23218210837916345}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:39:05,190] Trial 101 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.011895681579714322, 'n_estimators': 2542, 'max_depth': 15, 'subsample': 0.8244143273203247, 'colsample_bytree': 0.1731262917734843}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:39:15,457] Trial 102 finished with value: 0.966 and parameters: {'learning_rate': 0.01532268922315648, 'n_estimators': 2405, 'max_depth': 13, 'subsample': 0.8515678305554516, 'colsample_bytree': 0.14080285063159842}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:39:28,139] Trial 103 finished with value: 0.966 and parameters: {'learning_rate': 0.016713452974965043, 'n_estimators': 2446, 'max_depth': 14, 'subsample': 0.8682959218595154, 'colsample_bytree': 0.14148617005101968}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:39:40,116] Trial 104 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.02022642166434461, 'n_estimators': 2416, 'max_depth': 18, 'subsample': 0.8053264352120062, 'colsample_bytree': 0.14529574761403888}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:39:51,418] Trial 105 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.016003666820526195, 'n_estimators': 2351, 'max_depth': 15, 'subsample': 0.8932435018054825, 'colsample_bytree': 0.19165754273032415}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:40:03,058] Trial 106 finished with value: 0.962 and parameters: {'learning_rate': 0.024582383390547122, 'n_estimators': 2437, 'max_depth': 11, 'subsample': 0.8698219122187294, 'colsample_bytree': 0.17283186377555101}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:40:13,310] Trial 107 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.0334444491392705, 'n_estimators': 2019, 'max_depth': 16, 'subsample': 0.7401619774783033, 'colsample_bytree': 0.1592332859648391}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:40:21,777] Trial 108 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.014946958978151344, 'n_estimators': 2309, 'max_depth': 12, 'subsample': 0.9258295829672006, 'colsample_bytree': 0.10064170932733138}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:40:34,065] Trial 109 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.019906387521124145, 'n_estimators': 2084, 'max_depth': 14, 'subsample': 0.7900011320878818, 'colsample_bytree': 0.21181703156582526}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:40:47,610] Trial 110 finished with value: 0.958 and parameters: {'learning_rate': 0.030533667756416357, 'n_estimators': 2586, 'max_depth': 13, 'subsample': 0.7560372655486473, 'colsample_bytree': 0.2575321473128914}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:41:01,703] Trial 111 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.011411479226699847, 'n_estimators': 2743, 'max_depth': 14, 'subsample': 0.8550233565544804, 'colsample_bytree': 0.13671722566461272}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:41:09,850] Trial 112 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.017501854512919267, 'n_estimators': 2192, 'max_depth': 15, 'subsample': 0.838373337314304, 'colsample_bytree': 0.11682451969327323}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:41:23,687] Trial 113 finished with value: 0.962 and parameters: {'learning_rate': 0.013481615978437974, 'n_estimators': 2692, 'max_depth': 13, 'subsample': 0.8093115290157157, 'colsample_bytree': 0.1339652506103363}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:41:34,839] Trial 114 finished with value: 0.96 and parameters: {'learning_rate': 0.04525299408857139, 'n_estimators': 2476, 'max_depth': 12, 'subsample': 0.8638806369551492, 'colsample_bytree': 0.16383397197273372}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:41:38,498] Trial 115 finished with value: 0.962 and parameters: {'learning_rate': 0.022456610928201275, 'n_estimators': 734, 'max_depth': 10, 'subsample': 0.9107373916403474, 'colsample_bytree': 0.11392311131338859}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:41:55,188] Trial 116 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.009579703187933985, 'n_estimators': 2619, 'max_depth': 14, 'subsample': 0.882894016472884, 'colsample_bytree': 0.1932411006751953}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:42:05,942] Trial 117 finished with value: 0.966 and parameters: {'learning_rate': 0.026230333427759496, 'n_estimators': 2393, 'max_depth': 11, 'subsample': 0.7274260968696814, 'colsample_bytree': 0.14180502842839163}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:42:15,113] Trial 118 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.027624655384479828, 'n_estimators': 2390, 'max_depth': 11, 'subsample': 0.7238142883749796, 'colsample_bytree': 0.14848077216850472}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:42:26,767] Trial 119 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.03837002709116078, 'n_estimators': 2274, 'max_depth': 9, 'subsample': 0.6980526967183047, 'colsample_bytree': 0.23035935760616236}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:42:35,562] Trial 120 finished with value: 0.958 and parameters: {'learning_rate': 0.024962396811514537, 'n_estimators': 2206, 'max_depth': 11, 'subsample': 0.6423521008610207, 'colsample_bytree': 0.17308605193878285}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:42:47,433] Trial 121 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.016829368548202144, 'n_estimators': 2520, 'max_depth': 14, 'subsample': 0.7798471558012489, 'colsample_bytree': 0.132592906979035}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:42:58,822] Trial 122 finished with value: 0.958 and parameters: {'learning_rate': 0.03335140430069424, 'n_estimators': 2660, 'max_depth': 13, 'subsample': 0.6734302868073911, 'colsample_bytree': 0.10003974283090172}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:43:12,027] Trial 123 finished with value: 0.966 and parameters: {'learning_rate': 0.014653724769848215, 'n_estimators': 2774, 'max_depth': 16, 'subsample': 0.8473569578608855, 'colsample_bytree': 0.15569062453679341}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:43:23,088] Trial 124 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.01982358005360757, 'n_estimators': 2771, 'max_depth': 17, 'subsample': 0.7470846435040429, 'colsample_bytree': 0.15626361318434662}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:43:38,339] Trial 125 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.01506765519193126, 'n_estimators': 2838, 'max_depth': 16, 'subsample': 0.8165801046906597, 'colsample_bytree': 0.19800149297287306}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:43:53,372] Trial 126 finished with value: 0.966 and parameters: {'learning_rate': 0.008742298318649542, 'n_estimators': 2446, 'max_depth': 15, 'subsample': 0.7263021241006146, 'colsample_bytree': 0.17541806972667318}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:44:05,100] Trial 127 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.057961151275059415, 'n_estimators': 2461, 'max_depth': 18, 'subsample': 0.721035941287796, 'colsample_bytree': 0.21701770800364478}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:44:17,989] Trial 128 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.010758812768393253, 'n_estimators': 2360, 'max_depth': 8, 'subsample': 0.6894437354340862, 'colsample_bytree': 0.17052557019467635}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:44:29,048] Trial 129 finished with value: 0.96 and parameters: {'learning_rate': 0.028880053542287624, 'n_estimators': 2570, 'max_depth': 12, 'subsample': 0.7646569008050911, 'colsample_bytree': 0.24539332081842194}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:44:34,279] Trial 130 finished with value: 0.954 and parameters: {'learning_rate': 0.00851686152989202, 'n_estimators': 368, 'max_depth': 21, 'subsample': 0.7304241010144811, 'colsample_bytree': 0.18485379477319322}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:44:44,258] Trial 131 finished with value: 0.962 and parameters: {'learning_rate': 0.02201427321921672, 'n_estimators': 2499, 'max_depth': 15, 'subsample': 0.7935573687653799, 'colsample_bytree': 0.14776460181094986}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:44:55,772] Trial 132 finished with value: 0.966 and parameters: {'learning_rate': 0.013606911903250692, 'n_estimators': 2124, 'max_depth': 15, 'subsample': 0.7125425420572064, 'colsample_bytree': 0.13054405683360706}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:45:09,667] Trial 133 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.004719901354107996, 'n_estimators': 2122, 'max_depth': 16, 'subsample': 0.7074325962128195, 'colsample_bytree': 0.13822273646442076}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:45:20,605] Trial 134 finished with value: 0.966 and parameters: {'learning_rate': 0.006630077740384779, 'n_estimators': 1973, 'max_depth': 17, 'subsample': 0.6675196703319497, 'colsample_bytree': 0.1615795528316197}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:45:34,904] Trial 135 finished with value: 0.966 and parameters: {'learning_rate': 0.006425870436192096, 'n_estimators': 2297, 'max_depth': 17, 'subsample': 0.6652412135944995, 'colsample_bytree': 0.17893791085327482}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:45:49,341] Trial 136 finished with value: 0.966 and parameters: {'learning_rate': 0.006580104924514576, 'n_estimators': 1988, 'max_depth': 18, 'subsample': 0.6617778127841611, 'colsample_bytree': 0.203448440777879}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:46:03,486] Trial 137 finished with value: 0.966 and parameters: {'learning_rate': 0.0059042827196167, 'n_estimators': 1809, 'max_depth': 17, 'subsample': 0.6281718224050801, 'colsample_bytree': 0.1999673800887671}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:46:18,061] Trial 138 finished with value: 0.966 and parameters: {'learning_rate': 0.006380712753202805, 'n_estimators': 1938, 'max_depth': 19, 'subsample': 0.6618581496797402, 'colsample_bytree': 0.20901092778545505}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:46:32,961] Trial 139 finished with value: 0.966 and parameters: {'learning_rate': 0.004815964871123938, 'n_estimators': 2151, 'max_depth': 17, 'subsample': 0.607416320000052, 'colsample_bytree': 0.18508635495589076}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:46:46,192] Trial 140 finished with value: 0.966 and parameters: {'learning_rate': 0.008421578971083879, 'n_estimators': 1823, 'max_depth': 19, 'subsample': 0.6506697425609015, 'colsample_bytree': 0.2667957264613461}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:46:59,761] Trial 141 finished with value: 0.966 and parameters: {'learning_rate': 0.00575304296284803, 'n_estimators': 1940, 'max_depth': 19, 'subsample': 0.6671552697842618, 'colsample_bytree': 0.21177713611198828}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:47:14,770] Trial 142 finished with value: 0.966 and parameters: {'learning_rate': 0.006285704629920024, 'n_estimators': 1978, 'max_depth': 18, 'subsample': 0.6375379133500496, 'colsample_bytree': 0.2283811986585022}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:47:28,274] Trial 143 finished with value: 0.966 and parameters: {'learning_rate': 0.006774847676438731, 'n_estimators': 1881, 'max_depth': 21, 'subsample': 0.5936690228701919, 'colsample_bytree': 0.1995107179730873}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:47:43,687] Trial 144 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.0038440159638524754, 'n_estimators': 2045, 'max_depth': 17, 'subsample': 0.6252758542331671, 'colsample_bytree': 0.18273292432115834}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:47:54,479] Trial 145 finished with value: 0.966 and parameters: {'learning_rate': 0.008211172080943177, 'n_estimators': 1710, 'max_depth': 18, 'subsample': 0.6571427735826179, 'colsample_bytree': 0.16756542658130677}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:48:10,223] Trial 146 finished with value: 0.966 and parameters: {'learning_rate': 0.00715040570490928, 'n_estimators': 1981, 'max_depth': 16, 'subsample': 0.6637540874064193, 'colsample_bytree': 0.2953795170415162}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:48:25,082] Trial 147 finished with value: 0.9579999999999999 and parameters: {'learning_rate': 0.0031112466599096003, 'n_estimators': 1901, 'max_depth': 17, 'subsample': 0.6231018890719223, 'colsample_bytree': 0.2030895544475821}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:48:47,538] Trial 148 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.006020562785703709, 'n_estimators': 1794, 'max_depth': 20, 'subsample': 0.6840059095904034, 'colsample_bytree': 0.4579723010980101}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:48:58,068] Trial 149 finished with value: 0.966 and parameters: {'learning_rate': 0.009280223362585254, 'n_estimators': 1583, 'max_depth': 16, 'subsample': 0.6841399430797434, 'colsample_bytree': 0.2278949206991271}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:49:10,537] Trial 150 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.0105792019177399, 'n_estimators': 2102, 'max_depth': 19, 'subsample': 0.5868036313981375, 'colsample_bytree': 0.247748703832727}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:49:25,536] Trial 151 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.004677140752128193, 'n_estimators': 2152, 'max_depth': 17, 'subsample': 0.6281422589854654, 'colsample_bytree': 0.17666628241787266}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:49:39,926] Trial 152 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.005322074009598496, 'n_estimators': 2313, 'max_depth': 18, 'subsample': 0.6026983108671191, 'colsample_bytree': 0.1586230196454331}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:49:52,360] Trial 153 finished with value: 0.966 and parameters: {'learning_rate': 0.00702171201070361, 'n_estimators': 1721, 'max_depth': 17, 'subsample': 0.6471611729261448, 'colsample_bytree': 0.18852676471164773}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:50:06,559] Trial 154 finished with value: 0.966 and parameters: {'learning_rate': 0.00511307845659001, 'n_estimators': 2044, 'max_depth': 15, 'subsample': 0.6146046812071966, 'colsample_bytree': 0.20817568082776208}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:50:38,558] Trial 155 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.004107867757505373, 'n_estimators': 2161, 'max_depth': 16, 'subsample': 0.6790227543846841, 'colsample_bytree': 0.5508286005684537}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:50:48,207] Trial 156 finished with value: 0.966 and parameters: {'learning_rate': 0.008254653749954743, 'n_estimators': 1845, 'max_depth': 23, 'subsample': 0.5613738962681515, 'colsample_bytree': 0.15271409880793596}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:51:03,355] Trial 157 finished with value: 0.966 and parameters: {'learning_rate': 0.005956071788558632, 'n_estimators': 2225, 'max_depth': 7, 'subsample': 0.7056767548203252, 'colsample_bytree': 0.17510606376215018}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:51:15,829] Trial 158 finished with value: 0.966 and parameters: {'learning_rate': 0.01160754708689285, 'n_estimators': 1967, 'max_depth': 15, 'subsample': 0.6601336824577291, 'colsample_bytree': 0.19135369576957242}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:51:52,604] Trial 159 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.003505405999407901, 'n_estimators': 2291, 'max_depth': 17, 'subsample': 0.6382931007215541, 'colsample_bytree': 0.6233836015752434}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:52:20,203] Trial 160 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.001979638423513867, 'n_estimators': 2375, 'max_depth': 18, 'subsample': 0.5826246544678517, 'colsample_bytree': 0.33492833877122286}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:52:31,655] Trial 161 finished with value: 0.966 and parameters: {'learning_rate': 0.009137621307043015, 'n_estimators': 1819, 'max_depth': 20, 'subsample': 0.6548785622427846, 'colsample_bytree': 0.2633064562388849}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:52:44,897] Trial 162 finished with value: 0.966 and parameters: {'learning_rate': 0.008271965645245795, 'n_estimators': 2086, 'max_depth': 19, 'subsample': 0.6053029923938404, 'colsample_bytree': 0.21771167314730216}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:52:58,122] Trial 163 finished with value: 0.966 and parameters: {'learning_rate': 0.006821722329799891, 'n_estimators': 1919, 'max_depth': 16, 'subsample': 0.6988424149823222, 'colsample_bytree': 0.16272557925895476}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:53:15,928] Trial 164 finished with value: 0.966 and parameters: {'learning_rate': 0.004756920758012839, 'n_estimators': 1998, 'max_depth': 18, 'subsample': 0.6744714080829486, 'colsample_bytree': 0.26840345005749733}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:53:26,379] Trial 165 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.010318448232811092, 'n_estimators': 1647, 'max_depth': 19, 'subsample': 0.6475272887544204, 'colsample_bytree': 0.14251215247296822}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:53:37,993] Trial 166 finished with value: 0.962 and parameters: {'learning_rate': 0.012395248369831706, 'n_estimators': 2441, 'max_depth': 17, 'subsample': 0.715976611788283, 'colsample_bytree': 0.18157747755906645}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:53:50,023] Trial 167 finished with value: 0.966 and parameters: {'learning_rate': 0.008118848616869637, 'n_estimators': 1766, 'max_depth': 15, 'subsample': 0.6183442555803291, 'colsample_bytree': 0.23690258854058568}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:54:03,915] Trial 168 finished with value: 0.966 and parameters: {'learning_rate': 0.006306205733668158, 'n_estimators': 1866, 'max_depth': 16, 'subsample': 0.6695057074268157, 'colsample_bytree': 0.20062940844537683}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:54:15,394] Trial 169 finished with value: 0.96 and parameters: {'learning_rate': 0.013650532295476414, 'n_estimators': 2235, 'max_depth': 21, 'subsample': 0.6889245192837536, 'colsample_bytree': 0.12414008909369173}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:54:21,931] Trial 170 finished with value: 0.95 and parameters: {'learning_rate': 0.004835411467304727, 'n_estimators': 2134, 'max_depth': 19, 'subsample': 0.16481961040297427, 'colsample_bytree': 0.15599614275830626}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:54:37,485] Trial 171 finished with value: 0.966 and parameters: {'learning_rate': 0.005729427133918564, 'n_estimators': 2055, 'max_depth': 19, 'subsample': 0.6580611117355872, 'colsample_bytree': 0.20836864429871504}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:54:51,282] Trial 172 finished with value: 0.966 and parameters: {'learning_rate': 0.005472454340248951, 'n_estimators': 1953, 'max_depth': 17, 'subsample': 0.5397624287158449, 'colsample_bytree': 0.21623645077726944}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:55:02,222] Trial 173 finished with value: 0.966 and parameters: {'learning_rate': 0.00758496189542105, 'n_estimators': 1896, 'max_depth': 20, 'subsample': 0.6326339739697171, 'colsample_bytree': 0.17165083829118244}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:55:16,579] Trial 174 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.004154956220000675, 'n_estimators': 2025, 'max_depth': 18, 'subsample': 0.6668831187847007, 'colsample_bytree': 0.19285447729782182}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:55:25,943] Trial 175 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.009790581954984872, 'n_estimators': 1465, 'max_depth': 23, 'subsample': 0.715026349702603, 'colsample_bytree': 0.1393276312578974}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:55:40,739] Trial 176 finished with value: 0.966 and parameters: {'learning_rate': 0.006344503009210145, 'n_estimators': 1941, 'max_depth': 15, 'subsample': 0.599524254515164, 'colsample_bytree': 0.23781518693580067}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:55:52,709] Trial 177 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.015444580148965267, 'n_estimators': 2394, 'max_depth': 8, 'subsample': 0.6877612427543386, 'colsample_bytree': 0.17060411163686892}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:56:01,215] Trial 178 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.011738439780867357, 'n_estimators': 1849, 'max_depth': 19, 'subsample': 0.6376526055274008, 'colsample_bytree': 0.14791970428937581}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:56:16,590] Trial 179 finished with value: 0.962 and parameters: {'learning_rate': 0.003389998213254203, 'n_estimators': 2341, 'max_depth': 22, 'subsample': 0.7335461317161325, 'colsample_bytree': 0.11508908224076404}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:56:29,718] Trial 180 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.008132229178428464, 'n_estimators': 2174, 'max_depth': 17, 'subsample': 0.4054950780356571, 'colsample_bytree': 0.25437547603196825}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:56:44,033] Trial 181 finished with value: 0.966 and parameters: {'learning_rate': 0.006468605852293747, 'n_estimators': 1987, 'max_depth': 18, 'subsample': 0.6321994289973305, 'colsample_bytree': 0.22535693884724947}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:56:57,844] Trial 182 finished with value: 0.966 and parameters: {'learning_rate': 0.005298962232693101, 'n_estimators': 1945, 'max_depth': 18, 'subsample': 0.6527830955038796, 'colsample_bytree': 0.2147162937066388}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:57:10,880] Trial 183 finished with value: 0.966 and parameters: {'learning_rate': 0.0087527960796744, 'n_estimators': 1997, 'max_depth': 20, 'subsample': 0.6219238014465039, 'colsample_bytree': 0.27277539600013767}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:57:25,066] Trial 184 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.00420287768645867, 'n_estimators': 1784, 'max_depth': 17, 'subsample': 0.6742490304585063, 'colsample_bytree': 0.19201077901361907}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:57:44,189] Trial 185 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.006774939952471817, 'n_estimators': 2079, 'max_depth': 16, 'subsample': 0.5659801019857654, 'colsample_bytree': 0.4095363896293054}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:57:58,922] Trial 186 finished with value: 0.962 and parameters: {'learning_rate': 0.0027237213093104433, 'n_estimators': 2512, 'max_depth': 18, 'subsample': 0.45562759433466943, 'colsample_bytree': 0.16138227983418538}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:58:13,005] Trial 187 finished with value: 0.966 and parameters: {'learning_rate': 0.010019228009396969, 'n_estimators': 2431, 'max_depth': 16, 'subsample': 0.6377396813909361, 'colsample_bytree': 0.18042327719336793}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:58:30,116] Trial 188 finished with value: 0.966 and parameters: {'learning_rate': 0.005687452192448833, 'n_estimators': 2277, 'max_depth': 20, 'subsample': 0.654268321623214, 'colsample_bytree': 0.23665262247950325}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:58:41,693] Trial 189 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.017497680118762453, 'n_estimators': 1891, 'max_depth': 15, 'subsample': 0.6976165569768302, 'colsample_bytree': 0.20535060200870772}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:58:48,408] Trial 190 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.013648922189065982, 'n_estimators': 1734, 'max_depth': 19, 'subsample': 0.5852180265788932, 'colsample_bytree': 0.1285121974490815}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:59:01,731] Trial 191 finished with value: 0.966 and parameters: {'learning_rate': 0.006399900362150051, 'n_estimators': 1853, 'max_depth': 25, 'subsample': 0.6148619324381489, 'colsample_bytree': 0.197398045563189}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:59:15,130] Trial 192 finished with value: 0.966 and parameters: {'learning_rate': 0.007906482847427506, 'n_estimators': 1891, 'max_depth': 17, 'subsample': 0.6026442712979041, 'colsample_bytree': 0.22375965468564413}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:59:23,595] Trial 193 finished with value: 0.958 and parameters: {'learning_rate': 0.004752857953657253, 'n_estimators': 2019, 'max_depth': 21, 'subsample': 0.312243480837466, 'colsample_bytree': 0.18171110903757412}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 15:59:35,188] Trial 194 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.007173703872073321, 'n_estimators': 1826, 'max_depth': 19, 'subsample': 0.5953640255180642, 'colsample_bytree': 0.15659323652124646}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:00:05,503] Trial 195 finished with value: 0.9580000000000002 and parameters: {'learning_rate': 0.011061577145115062, 'n_estimators': 2102, 'max_depth': 18, 'subsample': 0.8825622920741184, 'colsample_bytree': 0.7211540122859116}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:00:20,406] Trial 196 finished with value: 0.966 and parameters: {'learning_rate': 0.005839136426346396, 'n_estimators': 1927, 'max_depth': 16, 'subsample': 0.6711371350278125, 'colsample_bytree': 0.1977259701938681}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:00:28,923] Trial 197 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.009690063731111377, 'n_estimators': 1668, 'max_depth': 14, 'subsample': 0.8453063068779613, 'colsample_bytree': 0.1417478495810782}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:00:45,029] Trial 198 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.0070617345302051455, 'n_estimators': 2636, 'max_depth': 21, 'subsample': 0.7042963258811843, 'colsample_bytree': 0.1686796111827601}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:00:59,818] Trial 199 finished with value: 0.958 and parameters: {'learning_rate': 0.004058071318020121, 'n_estimators': 2460, 'max_depth': 18, 'subsample': 0.36858212188186285, 'colsample_bytree': 0.21482329573862158}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:01:08,734] Trial 200 finished with value: 0.958 and parameters: {'learning_rate': 0.0050405833099836485, 'n_estimators': 886, 'max_depth': 9, 'subsample': 0.6362533208499619, 'colsample_bytree': 0.17976793918950906}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:01:17,143] Trial 201 finished with value: 0.966 and parameters: {'learning_rate': 0.008318504121684493, 'n_estimators': 1559, 'max_depth': 17, 'subsample': 0.652554179821141, 'colsample_bytree': 0.16078158177686716}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:01:29,288] Trial 202 finished with value: 0.96 and parameters: {'learning_rate': 0.006556733849437402, 'n_estimators': 1777, 'max_depth': 19, 'subsample': 0.666310151211357, 'colsample_bytree': 0.13290661545991983}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:01:39,401] Trial 203 finished with value: 0.966 and parameters: {'learning_rate': 0.008742759496850511, 'n_estimators': 1700, 'max_depth': 18, 'subsample': 0.6074593264741569, 'colsample_bytree': 0.16504468142350054}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:02:00,251] Trial 204 finished with value: 0.9480000000000001 and parameters: {'learning_rate': 0.0005168503908495731, 'n_estimators': 1822, 'max_depth': 46, 'subsample': 0.6829241948915021, 'colsample_bytree': 0.20488895280150746}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:02:09,466] Trial 205 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.012080192471636303, 'n_estimators': 1922, 'max_depth': 20, 'subsample': 0.647282789391032, 'colsample_bytree': 0.185549557766811}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:02:23,216] Trial 206 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.013810990789021158, 'n_estimators': 1746, 'max_depth': 15, 'subsample': 0.7440791917804568, 'colsample_bytree': 0.2902248000371028}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:02:35,586] Trial 207 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.007415102952458283, 'n_estimators': 1980, 'max_depth': 17, 'subsample': 0.5769387841109751, 'colsample_bytree': 0.14653246602287445}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:02:50,494] Trial 208 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.017540508287822335, 'n_estimators': 2351, 'max_depth': 33, 'subsample': 0.5040873807341549, 'colsample_bytree': 0.3659704878484601}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:02:52,360] Trial 209 finished with value: 0.9460000000000001 and parameters: {'learning_rate': 0.0054437405844221486, 'n_estimators': 147, 'max_depth': 22, 'subsample': 0.8701802575296148, 'colsample_bytree': 0.2315664338070908}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:03:03,988] Trial 210 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.009958823267793524, 'n_estimators': 2543, 'max_depth': 16, 'subsample': 0.5490086077303014, 'colsample_bytree': 0.11820729312607574}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:03:18,235] Trial 211 finished with value: 0.966 and parameters: {'learning_rate': 0.007199804163674385, 'n_estimators': 1981, 'max_depth': 16, 'subsample': 0.6656225618511897, 'colsample_bytree': 0.26136910683127257}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:03:31,902] Trial 212 finished with value: 0.966 and parameters: {'learning_rate': 0.00582709536666559, 'n_estimators': 1867, 'max_depth': 18, 'subsample': 0.6267291792886713, 'colsample_bytree': 0.24214345210672636}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:03:48,207] Trial 213 finished with value: 0.966 and parameters: {'learning_rate': 0.008421568575693778, 'n_estimators': 2028, 'max_depth': 8, 'subsample': 0.658173692494722, 'colsample_bytree': 0.2997220625935613}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:04:01,973] Trial 214 finished with value: 0.966 and parameters: {'learning_rate': 0.007050348721073866, 'n_estimators': 1933, 'max_depth': 17, 'subsample': 0.7259425931900807, 'colsample_bytree': 0.170479873989486}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:04:15,525] Trial 215 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.011194611431727173, 'n_estimators': 2146, 'max_depth': 15, 'subsample': 0.6929299963092425, 'colsample_bytree': 0.19744797405644907}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:04:29,197] Trial 216 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.004538138648408476, 'n_estimators': 1974, 'max_depth': 7, 'subsample': 0.6745857059372495, 'colsample_bytree': 0.14983162878717657}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:04:36,748] Trial 217 finished with value: 0.958 and parameters: {'learning_rate': 0.019847760705656328, 'n_estimators': 2087, 'max_depth': 14, 'subsample': 0.2721556301575463, 'colsample_bytree': 0.3206591237837486}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:04:49,515] Trial 218 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.015530044206248258, 'n_estimators': 2407, 'max_depth': 19, 'subsample': 0.34778241418490097, 'colsample_bytree': 0.27309612476454126}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:05:02,791] Trial 219 finished with value: 0.966 and parameters: {'learning_rate': 0.008894751265040152, 'n_estimators': 1828, 'max_depth': 41, 'subsample': 0.6475252665100847, 'colsample_bytree': 0.22276777906075584}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:05:16,607] Trial 220 finished with value: 0.966 and parameters: {'learning_rate': 0.006273725080185496, 'n_estimators': 2039, 'max_depth': 16, 'subsample': 0.7133146975684677, 'colsample_bytree': 0.18065166272129654}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:05:25,922] Trial 221 finished with value: 0.966 and parameters: {'learning_rate': 0.009354190688477995, 'n_estimators': 1477, 'max_depth': 16, 'subsample': 0.6869096912574014, 'colsample_bytree': 0.22990578326391192}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:05:39,536] Trial 222 finished with value: 0.966 and parameters: {'learning_rate': 0.007592921817284064, 'n_estimators': 1591, 'max_depth': 16, 'subsample': 0.683530194144757, 'colsample_bytree': 0.24711041320072774}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:05:53,054] Trial 223 finished with value: 0.966 and parameters: {'learning_rate': 0.005122695775005232, 'n_estimators': 1597, 'max_depth': 17, 'subsample': 0.6567561119703283, 'colsample_bytree': 0.20902859572200344}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:06:02,669] Trial 224 finished with value: 0.966 and parameters: {'learning_rate': 0.0124632781309678, 'n_estimators': 1662, 'max_depth': 18, 'subsample': 0.828972428927858, 'colsample_bytree': 0.19327837543530973}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:06:13,285] Trial 225 finished with value: 0.966 and parameters: {'learning_rate': 0.008948899115669175, 'n_estimators': 1749, 'max_depth': 15, 'subsample': 0.6324829961107625, 'colsample_bytree': 0.16603127935760464}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:06:25,766] Trial 226 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.0064256440396714375, 'n_estimators': 1884, 'max_depth': 14, 'subsample': 0.7030568199134404, 'colsample_bytree': 0.13916175540993408}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:06:46,243] Trial 227 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.0035270326637667124, 'n_estimators': 2589, 'max_depth': 18, 'subsample': 0.6188944288163668, 'colsample_bytree': 0.25449706000069483}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:06:59,805] Trial 228 finished with value: 0.96 and parameters: {'learning_rate': 0.043590875316981824, 'n_estimators': 2701, 'max_depth': 17, 'subsample': 0.8488693922386757, 'colsample_bytree': 0.29515601406148934}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:07:13,535] Trial 229 finished with value: 0.96 and parameters: {'learning_rate': 0.014362423469585389, 'n_estimators': 2474, 'max_depth': 10, 'subsample': 0.6676564255486785, 'colsample_bytree': 0.21664680643928844}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:07:23,326] Trial 230 finished with value: 0.952 and parameters: {'learning_rate': 1.2967553323639506e-05, 'n_estimators': 1246, 'max_depth': 13, 'subsample': 0.9020003153642022, 'colsample_bytree': 0.1555601048572111}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:07:36,159] Trial 231 finished with value: 0.966 and parameters: {'learning_rate': 0.006860038319976388, 'n_estimators': 1730, 'max_depth': 17, 'subsample': 0.6529884846422507, 'colsample_bytree': 0.19477449915440714}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:07:48,103] Trial 232 finished with value: 0.966 and parameters: {'learning_rate': 0.010584153756694447, 'n_estimators': 1814, 'max_depth': 16, 'subsample': 0.6409257205788442, 'colsample_bytree': 0.18109766931791804}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:08:05,270] Trial 233 finished with value: 0.966 and parameters: {'learning_rate': 0.007840533892101088, 'n_estimators': 1534, 'max_depth': 19, 'subsample': 0.5969920607637228, 'colsample_bytree': 0.48191747379333033}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:08:17,112] Trial 234 finished with value: 0.966 and parameters: {'learning_rate': 0.005354082633140732, 'n_estimators': 1720, 'max_depth': 15, 'subsample': 0.6844328355705402, 'colsample_bytree': 0.17252669941722418}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:08:30,540] Trial 235 finished with value: 0.966 and parameters: {'learning_rate': 0.006263951286381804, 'n_estimators': 1938, 'max_depth': 17, 'subsample': 0.7636507103082044, 'colsample_bytree': 0.20279799305377783}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:08:41,585] Trial 236 finished with value: 0.962 and parameters: {'learning_rate': 0.004663226943919164, 'n_estimators': 1655, 'max_depth': 20, 'subsample': 0.6403479457352128, 'colsample_bytree': 0.1271285603704629}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:09:00,007] Trial 237 finished with value: 0.9440000000000002 and parameters: {'learning_rate': 1.778852366887372e-05, 'n_estimators': 1805, 'max_depth': 18, 'subsample': 0.7234896447795076, 'colsample_bytree': 0.22512374448378972}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:09:20,776] Trial 238 finished with value: 0.952 and parameters: {'learning_rate': 5.356798434387401e-05, 'n_estimators': 2308, 'max_depth': 16, 'subsample': 0.6700317351280233, 'colsample_bytree': 0.18735922784043252}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:09:34,798] Trial 239 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.008039435320717901, 'n_estimators': 2410, 'max_depth': 9, 'subsample': 0.868972473904049, 'colsample_bytree': 0.1543790925109946}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:09:46,408] Trial 240 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.01087400602872222, 'n_estimators': 1864, 'max_depth': 19, 'subsample': 0.6197666560530095, 'colsample_bytree': 0.16589096041313878}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:10:00,970] Trial 241 finished with value: 0.966 and parameters: {'learning_rate': 0.0060716071607296185, 'n_estimators': 2025, 'max_depth': 15, 'subsample': 0.6171191129352653, 'colsample_bytree': 0.20600871427054734}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:10:18,395] Trial 242 finished with value: 0.966 and parameters: {'learning_rate': 0.004908546437604716, 'n_estimators': 2059, 'max_depth': 15, 'subsample': 0.5717863404927759, 'colsample_bytree': 0.2840531450412829}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:10:32,565] Trial 243 finished with value: 0.966 and parameters: {'learning_rate': 0.007317586037654415, 'n_estimators': 1969, 'max_depth': 17, 'subsample': 0.6053640408427081, 'colsample_bytree': 0.23541560964795052}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:10:48,700] Trial 244 finished with value: 0.966 and parameters: {'learning_rate': 0.005263451932127799, 'n_estimators': 2223, 'max_depth': 16, 'subsample': 0.6388070868073956, 'colsample_bytree': 0.21365289872537585}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:10:55,724] Trial 245 finished with value: 0.952 and parameters: {'learning_rate': 0.004235664018055291, 'n_estimators': 2105, 'max_depth': 14, 'subsample': 0.18238356122648408, 'colsample_bytree': 0.1879641439566109}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:11:07,880] Trial 246 finished with value: 0.966 and parameters: {'learning_rate': 0.009193056645774488, 'n_estimators': 1912, 'max_depth': 18, 'subsample': 0.6961732804527044, 'colsample_bytree': 0.14368808010258646}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:11:19,585] Trial 247 finished with value: 0.958 and parameters: {'learning_rate': 0.02259654395775241, 'n_estimators': 2510, 'max_depth': 13, 'subsample': 0.6606766679070385, 'colsample_bytree': 0.1778148894254655}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:11:25,494] Trial 248 finished with value: 0.954 and parameters: {'learning_rate': 0.03630768853713094, 'n_estimators': 1696, 'max_depth': 15, 'subsample': 0.2504922743902556, 'colsample_bytree': 0.20783141279234418}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:11:44,225] Trial 249 finished with value: 0.96 and parameters: {'learning_rate': 0.01755871635937463, 'n_estimators': 2788, 'max_depth': 17, 'subsample': 0.5855493940256952, 'colsample_bytree': 0.4568406680740771}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:11:57,639] Trial 250 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.006848074062695907, 'n_estimators': 1995, 'max_depth': 8, 'subsample': 0.44109855843970924, 'colsample_bytree': 0.2496259719039943}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:12:00,375] Trial 251 finished with value: 0.958 and parameters: {'learning_rate': 0.012610884633702012, 'n_estimators': 496, 'max_depth': 16, 'subsample': 0.6457262384226679, 'colsample_bytree': 0.11932845103507937}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:12:17,529] Trial 252 finished with value: 0.958 and parameters: {'learning_rate': 0.001818167978764816, 'n_estimators': 1888, 'max_depth': 18, 'subsample': 0.7452136561682956, 'colsample_bytree': 0.1620012514613849}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:12:33,505] Trial 253 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.005721002241237178, 'n_estimators': 1619, 'max_depth': 14, 'subsample': 0.8858189592927217, 'colsample_bytree': 0.22809999407185055}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:12:43,984] Trial 254 finished with value: 0.96 and parameters: {'learning_rate': 0.030558747720768865, 'n_estimators': 2021, 'max_depth': 25, 'subsample': 0.6752564901129485, 'colsample_bytree': 0.18448242847069465}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:13:01,489] Trial 255 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.008852659020433317, 'n_estimators': 1766, 'max_depth': 7, 'subsample': 0.8555004842559355, 'colsample_bytree': 0.34470799716152833}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:13:21,896] Trial 256 finished with value: 0.966 and parameters: {'learning_rate': 0.007303537331699593, 'n_estimators': 2175, 'max_depth': 5, 'subsample': 0.6132411025823301, 'colsample_bytree': 0.4341597842187644}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:13:38,924] Trial 257 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.003564434014555116, 'n_estimators': 2621, 'max_depth': 20, 'subsample': 0.706859202587921, 'colsample_bytree': 0.13504568491786445}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:13:50,944] Trial 258 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.015277036410870299, 'n_estimators': 2052, 'max_depth': 12, 'subsample': 0.6303977225029891, 'colsample_bytree': 0.20096828339913225}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:14:03,430] Trial 259 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.010368529868495742, 'n_estimators': 2449, 'max_depth': 17, 'subsample': 0.8361067663569749, 'colsample_bytree': 0.15481035333532941}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:14:12,999] Trial 260 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.020475929719506777, 'n_estimators': 2330, 'max_depth': 19, 'subsample': 0.6583367563740798, 'colsample_bytree': 0.10788007460026464}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:14:16,071] Trial 261 finished with value: 0.96 and parameters: {'learning_rate': 0.05180054166600742, 'n_estimators': 802, 'max_depth': 16, 'subsample': 0.4225610333263448, 'colsample_bytree': 0.17101075170263472}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:14:25,678] Trial 262 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.07959254156990495, 'n_estimators': 1938, 'max_depth': 15, 'subsample': 0.3816060768351103, 'colsample_bytree': 0.27285966164447695}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:14:47,499] Trial 263 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.005616891947096689, 'n_estimators': 2547, 'max_depth': 6, 'subsample': 0.5548147418194487, 'colsample_bytree': 0.3773969465221644}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:15:03,120] Trial 264 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.004496377564442564, 'n_estimators': 1100, 'max_depth': 11, 'subsample': 0.5301848529787752, 'colsample_bytree': 0.5067805475164994}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:15:16,594] Trial 265 finished with value: 0.9580000000000002 and parameters: {'learning_rate': 0.008191828354059225, 'n_estimators': 2382, 'max_depth': 17, 'subsample': 0.40052471371521703, 'colsample_bytree': 0.21832733722781603}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:15:34,176] Trial 266 finished with value: 0.958 and parameters: {'learning_rate': 0.01235896770604708, 'n_estimators': 2106, 'max_depth': 14, 'subsample': 0.8173967989717171, 'colsample_bytree': 0.3830734651674264}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:15:48,374] Trial 267 finished with value: 0.9460000000000001 and parameters: {'learning_rate': 0.00011593490799889044, 'n_estimators': 1834, 'max_depth': 9, 'subsample': 0.4679921291371768, 'colsample_bytree': 0.19257220122499882}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:16:06,654] Trial 268 finished with value: 0.966 and parameters: {'learning_rate': 0.006733811486090663, 'n_estimators': 2667, 'max_depth': 21, 'subsample': 0.678988930917785, 'colsample_bytree': 0.23929674490585942}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:16:19,840] Trial 269 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.00605834264269213, 'n_estimators': 1974, 'max_depth': 30, 'subsample': 0.7232602794160259, 'colsample_bytree': 0.1452070409580158}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:16:28,384] Trial 270 finished with value: 0.96 and parameters: {'learning_rate': 0.025135187270740704, 'n_estimators': 2272, 'max_depth': 18, 'subsample': 0.7865429665747568, 'colsample_bytree': 0.17344176763818936}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:16:38,835] Trial 271 finished with value: 0.958 and parameters: {'learning_rate': 0.009643517109354453, 'n_estimators': 1891, 'max_depth': 16, 'subsample': 0.3363427467913586, 'colsample_bytree': 0.1962294546941062}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:16:49,903] Trial 272 finished with value: 0.958 and parameters: {'learning_rate': 0.06486264490157549, 'n_estimators': 2489, 'max_depth': 13, 'subsample': 0.5961173991816233, 'colsample_bytree': 0.3135864862979695}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:16:56,317] Trial 273 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.017444505672850975, 'n_estimators': 1327, 'max_depth': 19, 'subsample': 0.6948952488731651, 'colsample_bytree': 0.1316055904958398}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:16:59,368] Trial 274 finished with value: 0.9460000000000001 and parameters: {'learning_rate': 0.0039201917625098165, 'n_estimators': 273, 'max_depth': 17, 'subsample': 0.6494517677137749, 'colsample_bytree': 0.30734100041715506}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:17:12,766] Trial 275 finished with value: 0.962 and parameters: {'learning_rate': 0.005045478814354755, 'n_estimators': 1953, 'max_depth': 15, 'subsample': 0.631248899371716, 'colsample_bytree': 0.1560374897680389}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:17:48,281] Trial 276 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.007295648859571656, 'n_estimators': 1784, 'max_depth': 18, 'subsample': 0.6662621103550083, 'colsample_bytree': 0.9988270073762946}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:17:55,904] Trial 277 finished with value: 0.954 and parameters: {'learning_rate': 0.013822890429250846, 'n_estimators': 2070, 'max_depth': 10, 'subsample': 0.10240752779228063, 'colsample_bytree': 0.26515539918620107}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:18:04,958] Trial 278 finished with value: 0.954 and parameters: {'learning_rate': 0.010868380790532345, 'n_estimators': 2749, 'max_depth': 16, 'subsample': 0.12519001341587124, 'colsample_bytree': 0.22086833909140213}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:18:20,512] Trial 279 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.008260742108780982, 'n_estimators': 2164, 'max_depth': 19, 'subsample': 0.9223696440830645, 'colsample_bytree': 0.1824331850036266}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:18:21,035] Trial 280 finished with value: 0.954 and parameters: {'learning_rate': 0.03536330722232356, 'n_estimators': 60, 'max_depth': 20, 'subsample': 0.4817940050966676, 'colsample_bytree': 0.1451431369251949}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:18:33,238] Trial 281 finished with value: 0.958 and parameters: {'learning_rate': 0.006146293200529958, 'n_estimators': 2420, 'max_depth': 22, 'subsample': 0.20168058783036497, 'colsample_bytree': 0.33244430472872755}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:18:39,729] Trial 282 finished with value: 0.952 and parameters: {'learning_rate': 0.005012228459752435, 'n_estimators': 2015, 'max_depth': 14, 'subsample': 0.14615255745909747, 'colsample_bytree': 0.2081242071900256}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:18:48,976] Trial 283 finished with value: 0.958 and parameters: {'learning_rate': 0.041958649839335956, 'n_estimators': 1686, 'max_depth': 15, 'subsample': 0.7641292425091054, 'colsample_bytree': 0.16506223489865046}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:19:08,383] Trial 284 finished with value: 0.9460000000000001 and parameters: {'learning_rate': 0.0009555266985645463, 'n_estimators': 1445, 'max_depth': 12, 'subsample': 0.8633980810596704, 'colsample_bytree': 0.25009560770885575}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:19:16,952] Trial 285 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.009356754377726916, 'n_estimators': 1566, 'max_depth': 16, 'subsample': 0.7376320318922643, 'colsample_bytree': 0.1299437884323234}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:19:28,361] Trial 286 finished with value: 0.958 and parameters: {'learning_rate': 0.002948431244704069, 'n_estimators': 1834, 'max_depth': 18, 'subsample': 0.7068403792785012, 'colsample_bytree': 0.11165297472332383}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:19:41,730] Trial 287 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.015183009474245193, 'n_estimators': 2595, 'max_depth': 17, 'subsample': 0.61503119378388, 'colsample_bytree': 0.17799900681746192}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:19:50,926] Trial 288 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.027921154713299333, 'n_estimators': 1899, 'max_depth': 13, 'subsample': 0.6869056289823935, 'colsample_bytree': 0.19849261840984372}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:20:04,937] Trial 289 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.02023198866711033, 'n_estimators': 2830, 'max_depth': 8, 'subsample': 0.8914505298428901, 'colsample_bytree': 0.22700334589466192}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:20:23,047] Trial 290 finished with value: 0.966 and parameters: {'learning_rate': 0.007653650519090765, 'n_estimators': 2360, 'max_depth': 17, 'subsample': 0.6544300210646471, 'colsample_bytree': 0.28348667556600926}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:20:41,588] Trial 291 finished with value: 0.95 and parameters: {'learning_rate': 0.00048671326251393556, 'n_estimators': 2541, 'max_depth': 19, 'subsample': 0.5101864806235603, 'colsample_bytree': 0.15902885397741237}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:21:08,587] Trial 292 finished with value: 0.9559999999999998 and parameters: {'learning_rate': 0.012056172503160842, 'n_estimators': 2228, 'max_depth': 10, 'subsample': 0.8112943229996962, 'colsample_bytree': 0.7540981813005863}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:21:20,446] Trial 293 finished with value: 0.96 and parameters: {'learning_rate': 0.0038142634420138817, 'n_estimators': 1985, 'max_depth': 41, 'subsample': 0.3099883651937184, 'colsample_bytree': 0.21200656563955633}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:21:32,774] Trial 294 finished with value: 0.966 and parameters: {'learning_rate': 0.006436295030763781, 'n_estimators': 1734, 'max_depth': 21, 'subsample': 0.6307719175238484, 'colsample_bytree': 0.1871800827612655}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:21:54,529] Trial 295 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.004467754415926788, 'n_estimators': 2110, 'max_depth': 16, 'subsample': 0.5786709192340429, 'colsample_bytree': 0.4241589605197865}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:22:08,493] Trial 296 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.010150515789548129, 'n_estimators': 2475, 'max_depth': 15, 'subsample': 0.8347084054326546, 'colsample_bytree': 0.14129757752704206}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:22:24,039] Trial 297 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.005605536750228114, 'n_estimators': 2040, 'max_depth': 18, 'subsample': 0.2861427548189973, 'colsample_bytree': 0.5661689696528179}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:22:41,754] Trial 298 finished with value: 0.966 and parameters: {'learning_rate': 0.008316111458387525, 'n_estimators': 2699, 'max_depth': 11, 'subsample': 0.6734533520863251, 'colsample_bytree': 0.24708443152678278}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:22:52,334] Trial 299 finished with value: 0.966 and parameters: {'learning_rate': 0.006639536893676058, 'n_estimators': 1634, 'max_depth': 20, 'subsample': 0.6458313855428938, 'colsample_bytree': 0.17146076399410698}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:23:00,861] Trial 300 finished with value: 0.952 and parameters: {'learning_rate': 0.09974204878008933, 'n_estimators': 1851, 'max_depth': 14, 'subsample': 0.35182382222097214, 'colsample_bytree': 0.6108937522504422}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:23:09,791] Trial 301 finished with value: 0.96 and parameters: {'learning_rate': 0.016851457094572364, 'n_estimators': 1939, 'max_depth': 17, 'subsample': 0.546632265748162, 'colsample_bytree': 0.10301779926882933}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:23:16,711] Trial 302 finished with value: 0.958 and parameters: {'learning_rate': 0.05556573340347289, 'n_estimators': 1761, 'max_depth': 16, 'subsample': 0.7178572058914208, 'colsample_bytree': 0.19385450194672724}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:23:28,178] Trial 303 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.023264461006357245, 'n_estimators': 2390, 'max_depth': 15, 'subsample': 0.60770195576245, 'colsample_bytree': 0.15293279403258733}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:23:34,821] Trial 304 finished with value: 0.9559999999999998 and parameters: {'learning_rate': 0.0025302632404555266, 'n_estimators': 1883, 'max_depth': 18, 'subsample': 0.23271561565635468, 'colsample_bytree': 0.125760751492618}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:23:48,616] Trial 305 finished with value: 0.966 and parameters: {'learning_rate': 0.012916248844789452, 'n_estimators': 2060, 'max_depth': 28, 'subsample': 0.750148602177874, 'colsample_bytree': 0.23306308610867152}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:23:54,284] Trial 306 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.007405108000954854, 'n_estimators': 646, 'max_depth': 9, 'subsample': 0.8717556743306797, 'colsample_bytree': 0.20590994951049474}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:24:06,480] Trial 307 finished with value: 0.958 and parameters: {'learning_rate': 0.00522277195786978, 'n_estimators': 970, 'max_depth': 19, 'subsample': 0.6899035081983073, 'colsample_bytree': 0.2959621666237776}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:24:22,218] Trial 308 finished with value: 0.95 and parameters: {'learning_rate': 3.304994753959223e-05, 'n_estimators': 1809, 'max_depth': 14, 'subsample': 0.6658284717375816, 'colsample_bytree': 0.17338439949988332}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:24:33,420] Trial 309 finished with value: 0.954 and parameters: {'learning_rate': 0.03127450645579966, 'n_estimators': 2632, 'max_depth': 17, 'subsample': 0.5935315357082176, 'colsample_bytree': 0.1452548803505937}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:24:44,460] Trial 310 finished with value: 0.966 and parameters: {'learning_rate': 0.009984193747981951, 'n_estimators': 2141, 'max_depth': 16, 'subsample': 0.6258461089327153, 'colsample_bytree': 0.2210880007511225}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:25:00,602] Trial 311 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.008747416101698751, 'n_estimators': 1983, 'max_depth': 49, 'subsample': 0.853743683897127, 'colsample_bytree': 0.2661128874616164}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:25:18,550] Trial 312 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.01168389603208704, 'n_estimators': 2453, 'max_depth': 12, 'subsample': 0.6527689690255818, 'colsample_bytree': 0.3402424421641478}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:25:39,816] Trial 313 finished with value: 0.962 and parameters: {'learning_rate': 0.006043149670128288, 'n_estimators': 2565, 'max_depth': 20, 'subsample': 0.9037942375604322, 'colsample_bytree': 0.1860679611396666}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:25:50,706] Trial 314 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.0044287737197452205, 'n_estimators': 1947, 'max_depth': 18, 'subsample': 0.5681699895597513, 'colsample_bytree': 0.16434147506802355}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:26:02,519] Trial 315 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.01499742822548851, 'n_estimators': 2283, 'max_depth': 15, 'subsample': 0.7313985820398071, 'colsample_bytree': 0.13244934385606946}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:26:41,978] Trial 316 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.0072677478159412934, 'n_estimators': 2317, 'max_depth': 13, 'subsample': 0.7016989838139921, 'colsample_bytree': 0.889287517179491}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:26:50,205] Trial 317 finished with value: 0.954 and parameters: {'learning_rate': 0.04345874837901467, 'n_estimators': 1515, 'max_depth': 16, 'subsample': 0.9533096031426365, 'colsample_bytree': 0.2008088296406943}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:27:07,301] Trial 318 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.02028127581351451, 'n_estimators': 2211, 'max_depth': 22, 'subsample': 0.6786004942564255, 'colsample_bytree': 0.5155083178365758}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:27:25,604] Trial 319 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.005342967096344405, 'n_estimators': 1682, 'max_depth': 17, 'subsample': 0.6384158632061222, 'colsample_bytree': 0.3843784103731258}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:27:42,071] Trial 320 finished with value: 0.958 and parameters: {'learning_rate': 0.003364946055521089, 'n_estimators': 2507, 'max_depth': 19, 'subsample': 0.6116982344261448, 'colsample_bytree': 0.1586894478784523}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:27:56,504] Trial 321 finished with value: 0.966 and parameters: {'learning_rate': 0.008554195321567842, 'n_estimators': 1909, 'max_depth': 9, 'subsample': 0.7111463992463274, 'colsample_bytree': 0.2315072858533041}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:28:08,672] Trial 322 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.0110543534586677, 'n_estimators': 2022, 'max_depth': 7, 'subsample': 0.6646183906380724, 'colsample_bytree': 0.18784585560986572}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:28:20,074] Trial 323 finished with value: 0.958 and parameters: {'learning_rate': 0.0063181433921766774, 'n_estimators': 2887, 'max_depth': 18, 'subsample': 0.4914302262060969, 'colsample_bytree': 0.11699029521024681}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:28:30,209] Trial 324 finished with value: 0.96 and parameters: {'learning_rate': 0.02694156687579096, 'n_estimators': 1786, 'max_depth': 15, 'subsample': 0.7760348495824058, 'colsample_bytree': 0.21123184251679353}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:28:47,351] Trial 325 finished with value: 0.958 and parameters: {'learning_rate': 0.014473833123162133, 'n_estimators': 1850, 'max_depth': 13, 'subsample': 0.8422406811214994, 'colsample_bytree': 0.44489846225073554}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:29:02,863] Trial 326 finished with value: 0.966 and parameters: {'learning_rate': 0.007456888347907552, 'n_estimators': 2103, 'max_depth': 17, 'subsample': 0.6428056362076369, 'colsample_bytree': 0.24933110816093496}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:29:39,318] Trial 327 finished with value: 0.954 and parameters: {'learning_rate': 0.001204714723325801, 'n_estimators': 2749, 'max_depth': 14, 'subsample': 0.5233935772708543, 'colsample_bytree': 0.3519206232212686}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:29:56,538] Trial 328 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.0041826736569419804, 'n_estimators': 2417, 'max_depth': 11, 'subsample': 0.6929363841678093, 'colsample_bytree': 0.16838820408874672}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:30:18,673] Trial 329 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.010109419235798662, 'n_estimators': 1966, 'max_depth': 16, 'subsample': 0.8260549083868839, 'colsample_bytree': 0.5333465450476449}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:30:30,264] Trial 330 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.017729072857263602, 'n_estimators': 2051, 'max_depth': 20, 'subsample': 0.8783823505095901, 'colsample_bytree': 0.14593786794154742}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:30:43,621] Trial 331 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.0051194666930332545, 'n_estimators': 1591, 'max_depth': 6, 'subsample': 0.8011294164807232, 'colsample_bytree': 0.1765876108794087}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:30:53,634] Trial 332 finished with value: 0.95 and parameters: {'learning_rate': 0.03366720471753489, 'n_estimators': 2669, 'max_depth': 14, 'subsample': 0.3909990438160907, 'colsample_bytree': 0.3237848189110006}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:31:06,583] Trial 333 finished with value: 0.96 and parameters: {'learning_rate': 0.008588300538931351, 'n_estimators': 2348, 'max_depth': 12, 'subsample': 0.7558538629284557, 'colsample_bytree': 0.1004315555570654}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:31:13,647] Trial 334 finished with value: 0.95 and parameters: {'learning_rate': 0.04864560016463306, 'n_estimators': 1918, 'max_depth': 15, 'subsample': 0.25969281374370135, 'colsample_bytree': 0.2163726396136452}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:31:27,042] Trial 335 finished with value: 0.966 and parameters: {'learning_rate': 0.0062816748090057896, 'n_estimators': 2165, 'max_depth': 19, 'subsample': 0.6221474371001754, 'colsample_bytree': 0.19525633203291148}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:31:38,467] Trial 336 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.007540394949278065, 'n_estimators': 1726, 'max_depth': 8, 'subsample': 0.6757566230191773, 'colsample_bytree': 0.12892189204439466}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:31:51,803] Trial 337 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.012684899692569402, 'n_estimators': 2539, 'max_depth': 21, 'subsample': 0.5948018276864034, 'colsample_bytree': 0.15544583660820793}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:32:09,565] Trial 338 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.004713475392876459, 'n_estimators': 1858, 'max_depth': 21, 'subsample': 0.737243710968623, 'colsample_bytree': 0.2622379196806499}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:32:17,069] Trial 339 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.022088417015094886, 'n_estimators': 1992, 'max_depth': 18, 'subsample': 0.43627835435609447, 'colsample_bytree': 0.17856418897299203}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:32:32,724] Trial 340 finished with value: 0.966 and parameters: {'learning_rate': 0.0093694007804471, 'n_estimators': 2451, 'max_depth': 16, 'subsample': 0.6569145979639405, 'colsample_bytree': 0.2380239721975011}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:32:55,700] Trial 341 finished with value: 0.966 and parameters: {'learning_rate': 0.006011016681500148, 'n_estimators': 2591, 'max_depth': 17, 'subsample': 0.7148513503890757, 'colsample_bytree': 0.279031457012987}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:33:01,453] Trial 342 finished with value: 0.958 and parameters: {'learning_rate': 0.018178111580674294, 'n_estimators': 1798, 'max_depth': 17, 'subsample': 0.31993594649741997, 'colsample_bytree': 0.13977188886010317}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:33:17,970] Trial 343 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.0035359220205050082, 'n_estimators': 2065, 'max_depth': 23, 'subsample': 0.6377599792976699, 'colsample_bytree': 0.20125411085374753}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:33:29,500] Trial 344 finished with value: 0.962 and parameters: {'learning_rate': 0.011484687852841565, 'n_estimators': 2264, 'max_depth': 18, 'subsample': 0.20354532402852954, 'colsample_bytree': 0.41869880893220324}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:33:41,973] Trial 345 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.007459915831185698, 'n_estimators': 1931, 'max_depth': 13, 'subsample': 0.9178708601426118, 'colsample_bytree': 0.16368198354921362}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:33:52,506] Trial 346 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.06335003433312117, 'n_estimators': 2384, 'max_depth': 15, 'subsample': 0.36960584739586705, 'colsample_bytree': 0.47242526185364564}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:34:09,719] Trial 347 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.02504856689724655, 'n_estimators': 1651, 'max_depth': 16, 'subsample': 0.853943540004414, 'colsample_bytree': 0.6878520444309472}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:34:32,382] Trial 348 finished with value: 0.958 and parameters: {'learning_rate': 0.005808172325843527, 'n_estimators': 2497, 'max_depth': 14, 'subsample': 0.9933888774945263, 'colsample_bytree': 0.22364579457155392}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:34:40,612] Trial 349 finished with value: 0.958 and parameters: {'learning_rate': 0.03680717036400919, 'n_estimators': 1999, 'max_depth': 19, 'subsample': 0.6904214403743462, 'colsample_bytree': 0.18740730628981617}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:34:55,852] Trial 350 finished with value: 0.9520000000000002 and parameters: {'learning_rate': 0.07795172677464561, 'n_estimators': 2793, 'max_depth': 20, 'subsample': 0.6141030322594668, 'colsample_bytree': 0.5979659836515046}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:35:07,354] Trial 351 finished with value: 0.966 and parameters: {'learning_rate': 0.01547158060825398, 'n_estimators': 2133, 'max_depth': 10, 'subsample': 0.888573002154, 'colsample_bytree': 0.12485636637288283}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:35:13,972] Trial 352 finished with value: 0.952 and parameters: {'learning_rate': 0.0095033412454619, 'n_estimators': 1761, 'max_depth': 17, 'subsample': 0.1396948045506172, 'colsample_bytree': 0.4896820773209314}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:35:32,979] Trial 353 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.004087800815287838, 'n_estimators': 1877, 'max_depth': 12, 'subsample': 0.6618298465196926, 'colsample_bytree': 0.30688378746277845}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:35:50,985] Trial 354 finished with value: 0.962 and parameters: {'learning_rate': 0.0023343750770832006, 'n_estimators': 2647, 'max_depth': 24, 'subsample': 0.5807017907737501, 'colsample_bytree': 0.15165565112539117}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:35:53,896] Trial 355 finished with value: 0.944 and parameters: {'learning_rate': 0.00685995851904196, 'n_estimators': 414, 'max_depth': 15, 'subsample': 0.160186366558767, 'colsample_bytree': 0.17686854217243966}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:36:06,131] Trial 356 finished with value: 0.9580000000000002 and parameters: {'learning_rate': 0.013638503133909156, 'n_estimators': 2194, 'max_depth': 7, 'subsample': 0.7998252862422284, 'colsample_bytree': 0.2128471161173588}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:36:28,738] Trial 357 finished with value: 0.942 and parameters: {'learning_rate': 1.6777393905930937e-05, 'n_estimators': 1407, 'max_depth': 19, 'subsample': 0.6734025865439374, 'colsample_bytree': 0.3943225699757569}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:36:39,445] Trial 358 finished with value: 0.9480000000000001 and parameters: {'learning_rate': 0.00019049988560929478, 'n_estimators': 2076, 'max_depth': 18, 'subsample': 0.28007691280745795, 'colsample_bytree': 0.24365810742764746}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:36:58,540] Trial 359 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.005176970107239038, 'n_estimators': 1709, 'max_depth': 16, 'subsample': 0.6462768607225534, 'colsample_bytree': 0.36518459213063537}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:37:16,500] Trial 360 finished with value: 0.9480000000000001 and parameters: {'learning_rate': 9.164891782881298e-05, 'n_estimators': 1822, 'max_depth': 10, 'subsample': 0.7235205756469061, 'colsample_bytree': 0.19605329219827705}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:37:25,320] Trial 361 finished with value: 0.952 and parameters: {'learning_rate': 0.008400520202876342, 'n_estimators': 2714, 'max_depth': 17, 'subsample': 0.12343823312873742, 'colsample_bytree': 0.1409081919983052}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:37:54,978] Trial 362 finished with value: 0.9580000000000002 and parameters: {'learning_rate': 0.0030281171998391204, 'n_estimators': 1928, 'max_depth': 18, 'subsample': 0.780042573711, 'colsample_bytree': 0.4135507984961072}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:38:03,692] Trial 363 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.029371374289908027, 'n_estimators': 2326, 'max_depth': 15, 'subsample': 0.6279079693860373, 'colsample_bytree': 0.1654088115084024}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:38:15,622] Trial 364 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.010565146557747013, 'n_estimators': 2418, 'max_depth': 5, 'subsample': 0.7029741771739341, 'colsample_bytree': 0.12220366877239394}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:38:37,602] Trial 365 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.00692145160708115, 'n_estimators': 2013, 'max_depth': 22, 'subsample': 0.45593452315227195, 'colsample_bytree': 0.6456885431336666}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:38:54,949] Trial 366 finished with value: 0.9480000000000001 and parameters: {'learning_rate': 0.00040752182243510715, 'n_estimators': 1872, 'max_depth': 16, 'subsample': 0.5668556492906258, 'colsample_bytree': 0.21154586320492905}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:39:21,191] Trial 367 finished with value: 0.954 and parameters: {'learning_rate': 0.001221966523646195, 'n_estimators': 2493, 'max_depth': 37, 'subsample': 0.8662407767088584, 'colsample_bytree': 0.18676022500821504}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:39:34,292] Trial 368 finished with value: 0.952 and parameters: {'learning_rate': 0.0007162281678642335, 'n_estimators': 1540, 'max_depth': 20, 'subsample': 0.545209738964928, 'colsample_bytree': 0.16181544573044296}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:39:49,348] Trial 369 finished with value: 0.96 and parameters: {'learning_rate': 0.004862433664363709, 'n_estimators': 2585, 'max_depth': 17, 'subsample': 0.2421813224441764, 'colsample_bytree': 0.4463093434492443}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:39:58,956] Trial 370 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.01961728812584551, 'n_estimators': 1966, 'max_depth': 11, 'subsample': 0.8266558886852532, 'colsample_bytree': 0.23150357269163652}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:40:16,874] Trial 371 finished with value: 0.966 and parameters: {'learning_rate': 0.005834384234064042, 'n_estimators': 2103, 'max_depth': 13, 'subsample': 0.682751853709719, 'colsample_bytree': 0.2629726216320418}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:40:48,752] Trial 372 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.0038487086854480605, 'n_estimators': 2226, 'max_depth': 9, 'subsample': 0.6535213701183152, 'colsample_bytree': 0.5450135881878013}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:40:58,184] Trial 373 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.008687211377619344, 'n_estimators': 1621, 'max_depth': 8, 'subsample': 0.47500080894813634, 'colsample_bytree': 0.14953529741854327}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:41:14,273] Trial 374 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.03997466768030655, 'n_estimators': 2029, 'max_depth': 14, 'subsample': 0.6088054360925129, 'colsample_bytree': 0.776685060399222}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:41:30,735] Trial 375 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.011508815858850422, 'n_estimators': 2360, 'max_depth': 28, 'subsample': 0.7478017368485065, 'colsample_bytree': 0.2895246564620262}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:41:36,565] Trial 376 finished with value: 0.9559999999999998 and parameters: {'learning_rate': 0.015995624149461152, 'n_estimators': 1765, 'max_depth': 19, 'subsample': 0.2899012980226906, 'colsample_bytree': 0.18567336027886489}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:42:35,358] Trial 377 finished with value: 0.942 and parameters: {'learning_rate': 1.2022363814917128e-05, 'n_estimators': 2959, 'max_depth': 24, 'subsample': 0.6322532022201042, 'colsample_bytree': 0.5823442380726247}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:42:42,379] Trial 378 finished with value: 0.954 and parameters: {'learning_rate': 0.00725039462462371, 'n_estimators': 1907, 'max_depth': 18, 'subsample': 0.26406586839562923, 'colsample_bytree': 0.2023207947713538}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:42:57,779] Trial 379 finished with value: 0.966 and parameters: {'learning_rate': 0.005554168332547906, 'n_estimators': 2448, 'max_depth': 16, 'subsample': 0.5927007692006345, 'colsample_bytree': 0.1744669838772499}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:43:23,268] Trial 380 finished with value: 0.9559999999999998 and parameters: {'learning_rate': 0.002219240166655159, 'n_estimators': 1809, 'max_depth': 21, 'subsample': 0.6695509796090198, 'colsample_bytree': 0.35038714252048153}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:43:43,625] Trial 381 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.003153813434134527, 'n_estimators': 1959, 'max_depth': 15, 'subsample': 0.9103558948243448, 'colsample_bytree': 0.22542151808317487}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:43:58,849] Trial 382 finished with value: 0.96 and parameters: {'learning_rate': 0.023760695548793127, 'n_estimators': 2284, 'max_depth': 12, 'subsample': 0.6963805574993849, 'colsample_bytree': 0.39847346650996424}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:44:18,569] Trial 383 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.013175868558578363, 'n_estimators': 2151, 'max_depth': 17, 'subsample': 0.8372301970337036, 'colsample_bytree': 0.47457849852778594}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:44:32,396] Trial 384 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.00922751757382166, 'n_estimators': 2536, 'max_depth': 14, 'subsample': 0.7638770138338673, 'colsample_bytree': 0.12984812399064755}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:44:46,790] Trial 385 finished with value: 0.966 and parameters: {'learning_rate': 0.0045958810283378195, 'n_estimators': 1860, 'max_depth': 16, 'subsample': 0.502605133895092, 'colsample_bytree': 0.2540265251620925}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:44:54,671] Trial 386 finished with value: 0.962 and parameters: {'learning_rate': 0.006526408857092352, 'n_estimators': 1695, 'max_depth': 20, 'subsample': 0.7277181812854017, 'colsample_bytree': 0.1086234698105801}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:45:05,006] Trial 387 finished with value: 0.946 and parameters: {'learning_rate': 0.04849067303004945, 'n_estimators': 2845, 'max_depth': 18, 'subsample': 0.10080117139161127, 'colsample_bytree': 0.14578546608579096}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:45:20,093] Trial 388 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.0075870073689081755, 'n_estimators': 2629, 'max_depth': 6, 'subsample': 0.6442853300798408, 'colsample_bytree': 0.16680085663582708}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:45:51,759] Trial 389 finished with value: 0.9559999999999998 and parameters: {'learning_rate': 0.001806311903048327, 'n_estimators': 2020, 'max_depth': 9, 'subsample': 0.8891126246381278, 'colsample_bytree': 0.3210850355126692}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:46:02,682] Trial 390 finished with value: 0.958 and parameters: {'learning_rate': 0.010670621813630612, 'n_estimators': 2721, 'max_depth': 19, 'subsample': 0.35645301495780024, 'colsample_bytree': 0.209818787657112}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:46:22,359] Trial 391 finished with value: 0.9480000000000001 and parameters: {'learning_rate': 0.0003134729786610834, 'n_estimators': 2083, 'max_depth': 17, 'subsample': 0.6200086031228266, 'colsample_bytree': 0.1882181976221327}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:46:31,436] Trial 392 finished with value: 0.954 and parameters: {'learning_rate': 0.018013275513721064, 'n_estimators': 2407, 'max_depth': 14, 'subsample': 0.29951544012191045, 'colsample_bytree': 0.23850354793976497}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:46:41,537] Trial 393 finished with value: 0.96 and parameters: {'learning_rate': 0.031270888669817164, 'n_estimators': 1921, 'max_depth': 27, 'subsample': 0.6669126909654273, 'colsample_bytree': 0.15642771270239353}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:47:01,633] Trial 394 finished with value: 0.966 and parameters: {'learning_rate': 0.00564094879775971, 'n_estimators': 2483, 'max_depth': 15, 'subsample': 0.7125406608684017, 'colsample_bytree': 0.2769011167760851}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:47:05,783] Trial 395 finished with value: 0.96 and parameters: {'learning_rate': 0.013544751966793198, 'n_estimators': 1151, 'max_depth': 7, 'subsample': 0.3324523200045384, 'colsample_bytree': 0.13632857134659337}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:47:20,052] Trial 396 finished with value: 0.966 and parameters: {'learning_rate': 0.00790917017186164, 'n_estimators': 1840, 'max_depth': 11, 'subsample': 0.8119851774635477, 'colsample_bytree': 0.20092849498525917}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:47:36,746] Trial 397 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.004056614681834659, 'n_estimators': 1982, 'max_depth': 46, 'subsample': 0.8525756034249887, 'colsample_bytree': 0.17545447615212229}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:47:54,772] Trial 398 finished with value: 0.9559999999999998 and parameters: {'learning_rate': 0.0014763048070882449, 'n_estimators': 1736, 'max_depth': 16, 'subsample': 0.6835161278077557, 'colsample_bytree': 0.21855895943355316}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:48:07,354] Trial 399 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.00959519348045296, 'n_estimators': 2356, 'max_depth': 18, 'subsample': 0.6533183286063301, 'colsample_bytree': 0.11440262002261156}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:48:24,383] Trial 400 finished with value: 0.962 and parameters: {'learning_rate': 0.002857619079191787, 'n_estimators': 2559, 'max_depth': 15, 'subsample': 0.6014313537658659, 'colsample_bytree': 0.1556231054465448}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:48:41,900] Trial 401 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.005073782318757415, 'n_estimators': 2193, 'max_depth': 35, 'subsample': 0.8723480560726518, 'colsample_bytree': 0.18877618586252948}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:48:57,241] Trial 402 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.022527635989244336, 'n_estimators': 2042, 'max_depth': 13, 'subsample': 0.6290727925315324, 'colsample_bytree': 0.49643851634234815}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:49:08,388] Trial 403 finished with value: 0.962 and parameters: {'learning_rate': 0.006292126533589748, 'n_estimators': 1899, 'max_depth': 21, 'subsample': 0.41674070758913057, 'colsample_bytree': 0.17400049779241109}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:49:27,857] Trial 404 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.015322207159561736, 'n_estimators': 1959, 'max_depth': 17, 'subsample': 0.9304514893389944, 'colsample_bytree': 0.521971804618952}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:49:43,415] Trial 405 finished with value: 0.966 and parameters: {'learning_rate': 0.011227032695603788, 'n_estimators': 1816, 'max_depth': 19, 'subsample': 0.6929470925868267, 'colsample_bytree': 0.3609414439812028}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:49:44,840] Trial 406 finished with value: 0.958 and parameters: {'learning_rate': 0.00806714129326571, 'n_estimators': 263, 'max_depth': 16, 'subsample': 0.38500403583426235, 'colsample_bytree': 0.13601595461652483}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:49:59,009] Trial 407 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.007165698300548693, 'n_estimators': 1630, 'max_depth': 31, 'subsample': 0.7838339664668239, 'colsample_bytree': 0.2346238911387198}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:50:30,892] Trial 408 finished with value: 0.944 and parameters: {'learning_rate': 0.00025708484300982046, 'n_estimators': 2300, 'max_depth': 10, 'subsample': 0.5286641396241021, 'colsample_bytree': 0.42700302259937173}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:50:52,610] Trial 409 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.0035903001521731914, 'n_estimators': 2423, 'max_depth': 41, 'subsample': 0.9458789251931599, 'colsample_bytree': 0.19930126438821238}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:51:04,425] Trial 410 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.06028666489860459, 'n_estimators': 2660, 'max_depth': 18, 'subsample': 0.6667663937033625, 'colsample_bytree': 0.21545013773676203}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:51:13,013] Trial 411 finished with value: 0.962 and parameters: {'learning_rate': 0.009269233894858234, 'n_estimators': 2512, 'max_depth': 15, 'subsample': 0.19831640205285617, 'colsample_bytree': 0.29700039082979846}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:51:26,906] Trial 412 finished with value: 0.9400000000000001 and parameters: {'learning_rate': 0.0006850943644029538, 'n_estimators': 2129, 'max_depth': 17, 'subsample': 0.17162388751616509, 'colsample_bytree': 0.43809039898886004}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:51:42,853] Trial 413 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.0065254886463871715, 'n_estimators': 2796, 'max_depth': 12, 'subsample': 0.6361215690734748, 'colsample_bytree': 0.15578306574035042}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:51:52,813] Trial 414 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.020056042096178096, 'n_estimators': 1775, 'max_depth': 8, 'subsample': 0.22553817658386816, 'colsample_bytree': 0.47007954231895743}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:52:11,586] Trial 415 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.004633279583331223, 'n_estimators': 2067, 'max_depth': 20, 'subsample': 0.7355951227388237, 'colsample_bytree': 0.25583315375540744}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:52:18,873] Trial 416 finished with value: 0.96 and parameters: {'learning_rate': 0.027980053861862995, 'n_estimators': 1887, 'max_depth': 13, 'subsample': 0.7119908647514814, 'colsample_bytree': 0.17693465630414115}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:52:28,681] Trial 417 finished with value: 0.9540000000000001 and parameters: {'learning_rate': 0.07461144485811383, 'n_estimators': 2255, 'max_depth': 14, 'subsample': 0.5622692700492399, 'colsample_bytree': 0.12482352937462524}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:52:44,710] Trial 418 finished with value: 0.96 and parameters: {'learning_rate': 0.03913158669506278, 'n_estimators': 1949, 'max_depth': 19, 'subsample': 0.5878582784267227, 'colsample_bytree': 0.8029107235595105}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:52:48,524] Trial 419 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.012903814816330936, 'n_estimators': 561, 'max_depth': 16, 'subsample': 0.651223217936936, 'colsample_bytree': 0.20037246606638}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:53:00,202] Trial 420 finished with value: 0.962 and parameters: {'learning_rate': 0.005731504599713424, 'n_estimators': 1667, 'max_depth': 18, 'subsample': 0.6066713474023762, 'colsample_bytree': 0.14954605523142148}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:53:32,834] Trial 421 finished with value: 0.9559999999999998 and parameters: {'learning_rate': 0.001496768987112984, 'n_estimators': 2586, 'max_depth': 17, 'subsample': 0.6836839574283484, 'colsample_bytree': 0.3240804860322188}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:53:54,680] Trial 422 finished with value: 0.954 and parameters: {'learning_rate': 0.016698424228248968, 'n_estimators': 1993, 'max_depth': 22, 'subsample': 0.9766276738894394, 'colsample_bytree': 0.6360259555963956}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:54:07,810] Trial 423 finished with value: 0.966 and parameters: {'learning_rate': 0.008595050571625485, 'n_estimators': 1471, 'max_depth': 16, 'subsample': 0.8412386298301295, 'colsample_bytree': 0.2209347880176421}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:54:20,630] Trial 424 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.011210675531539566, 'n_estimators': 2118, 'max_depth': 14, 'subsample': 0.7515225310098506, 'colsample_bytree': 0.164482886875513}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:54:37,342] Trial 425 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.0067077807635658225, 'n_estimators': 1865, 'max_depth': 19, 'subsample': 0.4049093051545902, 'colsample_bytree': 0.5336097143643015}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:55:12,425] Trial 426 finished with value: 0.9400000000000001 and parameters: {'learning_rate': 8.021200911206432e-05, 'n_estimators': 2446, 'max_depth': 15, 'subsample': 0.44397675837326817, 'colsample_bytree': 0.5794234098335119}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:55:33,332] Trial 427 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.004332680186014733, 'n_estimators': 2748, 'max_depth': 8, 'subsample': 0.893888721610953, 'colsample_bytree': 0.18640315501399096}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:55:52,417] Trial 428 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.005121977839663819, 'n_estimators': 1717, 'max_depth': 12, 'subsample': 0.6219156785958263, 'colsample_bytree': 0.40228718564444}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:56:34,225] Trial 429 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.002740535611483395, 'n_estimators': 2009, 'max_depth': 13, 'subsample': 0.6495078898152462, 'colsample_bytree': 0.6866151325430787}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:56:52,323] Trial 430 finished with value: 0.96 and parameters: {'learning_rate': 0.025621687621487005, 'n_estimators': 2337, 'max_depth': 18, 'subsample': 0.795944528452183, 'colsample_bytree': 0.5669288894937226}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:57:01,877] Trial 431 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.010140256608368788, 'n_estimators': 1921, 'max_depth': 23, 'subsample': 0.673298684721163, 'colsample_bytree': 0.11731278375532503}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:57:34,823] Trial 432 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.00786535496965357, 'n_estimators': 2184, 'max_depth': 26, 'subsample': 0.8611256418090889, 'colsample_bytree': 0.6657741443808446}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:57:45,419] Trial 433 finished with value: 0.966 and parameters: {'learning_rate': 0.014101367647462138, 'n_estimators': 1797, 'max_depth': 30, 'subsample': 0.7069193984077413, 'colsample_bytree': 0.2366530398638445}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:57:55,567] Trial 434 finished with value: 0.958 and parameters: {'learning_rate': 0.08692938014690367, 'n_estimators': 2380, 'max_depth': 17, 'subsample': 0.7273172691522286, 'colsample_bytree': 0.1414869354521472}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:58:14,849] Trial 435 finished with value: 0.954 and parameters: {'learning_rate': 0.002136398794924615, 'n_estimators': 1579, 'max_depth': 20, 'subsample': 0.7726017913085286, 'colsample_bytree': 0.2720331454150681}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:58:20,805] Trial 436 finished with value: 0.9480000000000001 and parameters: {'learning_rate': 0.03537405780644843, 'n_estimators': 2061, 'max_depth': 9, 'subsample': 0.323731269361335, 'colsample_bytree': 0.1018197734579497}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:58:23,774] Trial 437 finished with value: 0.9480000000000001 and parameters: {'learning_rate': 1.0789580622326692e-05, 'n_estimators': 139, 'max_depth': 11, 'subsample': 0.8274672587514509, 'colsample_bytree': 0.2059850957375547}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:58:34,188] Trial 438 finished with value: 0.952 and parameters: {'learning_rate': 0.047519161377426, 'n_estimators': 2695, 'max_depth': 16, 'subsample': 0.662364502220903, 'colsample_bytree': 0.172990805895748}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:59:01,551] Trial 439 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.00601340536414268, 'n_estimators': 2520, 'max_depth': 21, 'subsample': 0.6400004035718495, 'colsample_bytree': 0.458744804610718}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:59:18,800] Trial 440 finished with value: 0.96 and parameters: {'learning_rate': 0.02067340675032655, 'n_estimators': 2610, 'max_depth': 15, 'subsample': 0.514737733849455, 'colsample_bytree': 0.5036395579268956}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:59:26,259] Trial 441 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.012300829073955653, 'n_estimators': 1835, 'max_depth': 24, 'subsample': 0.4205169413355544, 'colsample_bytree': 0.19346608075986818}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:59:37,953] Trial 442 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.008808471251193934, 'n_estimators': 1999, 'max_depth': 17, 'subsample': 0.49180587707939377, 'colsample_bytree': 0.16323600912124536}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 16:59:54,893] Trial 443 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.0066515963507541844, 'n_estimators': 2248, 'max_depth': 26, 'subsample': 0.6880686029128524, 'colsample_bytree': 0.2527080528015106}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:00:07,670] Trial 444 finished with value: 0.958 and parameters: {'learning_rate': 0.003700294046342946, 'n_estimators': 2450, 'max_depth': 14, 'subsample': 0.3623270944979341, 'colsample_bytree': 0.13638023047050526}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:00:23,567] Trial 445 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.01665718466800409, 'n_estimators': 1932, 'max_depth': 18, 'subsample': 0.6118310352762741, 'colsample_bytree': 0.489398949767464}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:00:35,559] Trial 446 finished with value: 0.966 and parameters: {'learning_rate': 0.0050623795698616055, 'n_estimators': 1751, 'max_depth': 16, 'subsample': 0.5836103014162416, 'colsample_bytree': 0.21494132752967915}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:00:47,587] Trial 447 finished with value: 0.966 and parameters: {'learning_rate': 0.0074236726103817105, 'n_estimators': 2055, 'max_depth': 15, 'subsample': 0.5528436755688344, 'colsample_bytree': 0.18179812148805383}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:00:58,933] Trial 448 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.009333952663335636, 'n_estimators': 1341, 'max_depth': 19, 'subsample': 0.8811493288881568, 'colsample_bytree': 0.15125263100686265}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:01:16,753] Trial 449 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.005475647607822805, 'n_estimators': 1884, 'max_depth': 12, 'subsample': 0.9086308540371772, 'colsample_bytree': 0.22603309449664377}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:01:33,623] Trial 450 finished with value: 0.966 and parameters: {'learning_rate': 0.011490084513582825, 'n_estimators': 2135, 'max_depth': 16, 'subsample': 0.6991527766082624, 'colsample_bytree': 0.34233654845968853}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:01:40,995] Trial 451 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.03097436874465038, 'n_estimators': 1683, 'max_depth': 10, 'subsample': 0.6333038609779644, 'colsample_bytree': 0.19406429625385113}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:02:06,083] Trial 452 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.006995095450432671, 'n_estimators': 2881, 'max_depth': 17, 'subsample': 0.812425450565854, 'colsample_bytree': 0.3074315455481213}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:02:25,434] Trial 453 finished with value: 0.96 and parameters: {'learning_rate': 0.004282114299891956, 'n_estimators': 2391, 'max_depth': 18, 'subsample': 0.999878901167048, 'colsample_bytree': 0.16847131544319335}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:02:42,945] Trial 454 finished with value: 0.944 and parameters: {'learning_rate': 0.0006779366986275063, 'n_estimators': 1537, 'max_depth': 13, 'subsample': 0.6725489675394398, 'colsample_bytree': 0.2435482447288727}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:02:55,148] Trial 455 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.008260124574956363, 'n_estimators': 1969, 'max_depth': 20, 'subsample': 0.6512953445391136, 'colsample_bytree': 0.12275912206359382}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:03:03,242] Trial 456 finished with value: 0.924 and parameters: {'learning_rate': 0.00016972284928547257, 'n_estimators': 2481, 'max_depth': 11, 'subsample': 0.12233244428543727, 'colsample_bytree': 0.14176937600460204}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:03:30,361] Trial 457 finished with value: 0.9460000000000001 and parameters: {'learning_rate': 4.3233664575310653e-05, 'n_estimators': 2547, 'max_depth': 15, 'subsample': 0.7365842214167643, 'colsample_bytree': 0.20452552273714886}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:03:45,361] Trial 458 finished with value: 0.958 and parameters: {'learning_rate': 0.05618204120323538, 'n_estimators': 2320, 'max_depth': 22, 'subsample': 0.848386904045061, 'colsample_bytree': 0.6090172042067623}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:04:35,118] Trial 459 finished with value: 0.942 and parameters: {'learning_rate': 0.0002574169215298655, 'n_estimators': 1800, 'max_depth': 17, 'subsample': 0.6199149517741617, 'colsample_bytree': 0.8567531709056163}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:04:43,583] Trial 460 finished with value: 0.96 and parameters: {'learning_rate': 0.01902001731075237, 'n_estimators': 1881, 'max_depth': 16, 'subsample': 0.7172759571988698, 'colsample_bytree': 0.1784929449265256}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:04:57,777] Trial 461 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.010207427481404411, 'n_estimators': 2668, 'max_depth': 7, 'subsample': 0.7550165151239453, 'colsample_bytree': 0.16055472614095243}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:05:08,024] Trial 462 finished with value: 0.9480000000000001 and parameters: {'learning_rate': 0.001013633929301518, 'n_estimators': 843, 'max_depth': 5, 'subsample': 0.6617197367887955, 'colsample_bytree': 0.22529963718908735}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:05:18,868] Trial 463 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.01328634806478912, 'n_estimators': 2094, 'max_depth': 14, 'subsample': 0.6805120158777322, 'colsample_bytree': 0.1844715639676488}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:05:26,597] Trial 464 finished with value: 0.96 and parameters: {'learning_rate': 0.005832285992029958, 'n_estimators': 2019, 'max_depth': 19, 'subsample': 0.2508519147316403, 'colsample_bytree': 0.10055293861775336}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:05:39,546] Trial 465 finished with value: 0.958 and parameters: {'learning_rate': 0.0030372314543094083, 'n_estimators': 1969, 'max_depth': 18, 'subsample': 0.3077523164938517, 'colsample_bytree': 0.2761188933370844}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:06:02,385] Trial 466 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.015391673793829812, 'n_estimators': 1836, 'max_depth': 17, 'subsample': 0.5961407833434629, 'colsample_bytree': 0.9571079326409855}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:06:10,873] Trial 467 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.02594704236997827, 'n_estimators': 1636, 'max_depth': 8, 'subsample': 0.5716043686753298, 'colsample_bytree': 0.13142923920376395}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:06:20,313] Trial 468 finished with value: 0.962 and parameters: {'learning_rate': 0.0066465914545079, 'n_estimators': 2212, 'max_depth': 15, 'subsample': 0.3493478083910439, 'colsample_bytree': 0.20841973441392544}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:06:35,707] Trial 469 finished with value: 0.9359999999999999 and parameters: {'learning_rate': 3.528730160711923e-05, 'n_estimators': 1929, 'max_depth': 9, 'subsample': 0.29706523548876645, 'colsample_bytree': 0.3847036067736057}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:06:43,309] Trial 470 finished with value: 0.952 and parameters: {'learning_rate': 0.004828552090173377, 'n_estimators': 667, 'max_depth': 19, 'subsample': 0.8743369322543625, 'colsample_bytree': 0.15379851268616407}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:07:04,888] Trial 471 finished with value: 0.966 and parameters: {'learning_rate': 0.008226096969005819, 'n_estimators': 2593, 'max_depth': 21, 'subsample': 0.6371450097628969, 'colsample_bytree': 0.40538190553222075}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:07:21,343] Trial 472 finished with value: 0.958 and parameters: {'learning_rate': 0.022076288247626266, 'n_estimators': 2778, 'max_depth': 16, 'subsample': 0.9562965078661354, 'colsample_bytree': 0.29327642227344547}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:07:40,641] Trial 473 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.0025857596514595755, 'n_estimators': 2429, 'max_depth': 13, 'subsample': 0.27637979288953507, 'colsample_bytree': 0.5495812491795198}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:07:52,820] Trial 474 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.010318179600344514, 'n_estimators': 1715, 'max_depth': 20, 'subsample': 0.5425309318264228, 'colsample_bytree': 0.2514781617327616}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:08:31,347] Trial 475 finished with value: 0.942 and parameters: {'learning_rate': 0.00012441647096007839, 'n_estimators': 2026, 'max_depth': 18, 'subsample': 0.693475303045718, 'colsample_bytree': 0.5123740948676679}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:08:47,505] Trial 476 finished with value: 0.966 and parameters: {'learning_rate': 0.006278750340334844, 'n_estimators': 2494, 'max_depth': 17, 'subsample': 0.6568984520911225, 'colsample_bytree': 0.19155345984275382}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:09:04,519] Trial 477 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.0036891855311746804, 'n_estimators': 2152, 'max_depth': 14, 'subsample': 0.8214554503657376, 'colsample_bytree': 0.16961126343647118}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:09:42,610] Trial 478 finished with value: 0.942 and parameters: {'learning_rate': 0.00015203140283033938, 'n_estimators': 2290, 'max_depth': 11, 'subsample': 0.6239526696437993, 'colsample_bytree': 0.45811770353743775}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:10:03,211] Trial 479 finished with value: 0.96 and parameters: {'learning_rate': 0.011853191874775784, 'n_estimators': 2387, 'max_depth': 15, 'subsample': 0.44510903132184976, 'colsample_bytree': 0.621155924102159}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:10:18,604] Trial 480 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.007643541670044251, 'n_estimators': 1883, 'max_depth': 6, 'subsample': 0.6060509769508776, 'colsample_bytree': 0.33610669321193876}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:10:27,641] Trial 481 finished with value: 0.96 and parameters: {'learning_rate': 0.005433877288289762, 'n_estimators': 1790, 'max_depth': 18, 'subsample': 0.39205140506703456, 'colsample_bytree': 0.23412987275724695}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:10:37,565] Trial 482 finished with value: 0.958 and parameters: {'learning_rate': 0.046719084077800864, 'n_estimators': 2088, 'max_depth': 16, 'subsample': 0.7654956751754919, 'colsample_bytree': 0.140233906816622}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:10:43,956] Trial 483 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.03708995687856871, 'n_estimators': 1963, 'max_depth': 33, 'subsample': 0.708532095468103, 'colsample_bytree': 0.1186345563917263}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:10:59,126] Trial 484 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.014192609812082866, 'n_estimators': 2652, 'max_depth': 14, 'subsample': 0.791784194524997, 'colsample_bytree': 0.21646860416500666}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:11:22,995] Trial 485 finished with value: 0.9580000000000002 and parameters: {'learning_rate': 0.0175056576106608, 'n_estimators': 2736, 'max_depth': 19, 'subsample': 0.8563135102967145, 'colsample_bytree': 0.5587020838615142}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:11:31,947] Trial 486 finished with value: 0.952 and parameters: {'learning_rate': 0.07014651545151182, 'n_estimators': 1856, 'max_depth': 12, 'subsample': 0.37715112215591906, 'colsample_bytree': 0.5307773458509738}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:11:56,128] Trial 487 finished with value: 0.958 and parameters: {'learning_rate': 0.008616431078097484, 'n_estimators': 2538, 'max_depth': 23, 'subsample': 0.9306518078579824, 'colsample_bytree': 0.36083251743401046}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:12:07,755] Trial 488 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.0046482756667384495, 'n_estimators': 1738, 'max_depth': 25, 'subsample': 0.6774655964929291, 'colsample_bytree': 0.16916711009675872}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:12:22,776] Trial 489 finished with value: 0.966 and parameters: {'learning_rate': 0.006511939127605876, 'n_estimators': 1919, 'max_depth': 10, 'subsample': 0.7331123051541449, 'colsample_bytree': 0.20186070286918406}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:12:29,500] Trial 490 finished with value: 0.9560000000000001 and parameters: {'learning_rate': 0.009805076818701521, 'n_estimators': 1589, 'max_depth': 17, 'subsample': 0.2113912258757309, 'colsample_bytree': 0.1510932390403078}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:12:47,543] Trial 491 finished with value: 0.954 and parameters: {'learning_rate': 0.0014832164590098638, 'n_estimators': 2029, 'max_depth': 9, 'subsample': 0.6399180250657948, 'colsample_bytree': 0.18418029907705036}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:13:06,384] Trial 492 finished with value: 0.9559999999999998 and parameters: {'learning_rate': 0.002208210610403526, 'n_estimators': 2467, 'max_depth': 13, 'subsample': 0.4557948031484288, 'colsample_bytree': 0.26100034010389583}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:13:13,681] Trial 493 finished with value: 0.954 and parameters: {'learning_rate': 0.02330331493814782, 'n_estimators': 2340, 'max_depth': 29, 'subsample': 0.24146877124755056, 'colsample_bytree': 0.231249809573006}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:13:26,604] Trial 494 finished with value: 0.962 and parameters: {'learning_rate': 0.007237823995619081, 'n_estimators': 2204, 'max_depth': 16, 'subsample': 0.6621214912076931, 'colsample_bytree': 0.12574947752294918}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:14:10,916] Trial 495 finished with value: 0.9400000000000001 and parameters: {'learning_rate': 1.722262467600287e-05, 'n_estimators': 2089, 'max_depth': 18, 'subsample': 0.6897998491890727, 'colsample_bytree': 0.5853953492204623}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:14:28,224] Trial 496 finished with value: 0.9620000000000001 and parameters: {'learning_rate': 0.0032867031295619486, 'n_estimators': 1971, 'max_depth': 8, 'subsample': 0.9046000665958371, 'colsample_bytree': 0.16124886245689318}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:14:33,313] Trial 497 finished with value: 0.954 and parameters: {'learning_rate': 0.005420724672794197, 'n_estimators': 753, 'max_depth': 48, 'subsample': 0.576924972184267, 'colsample_bytree': 0.18957624308756887}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:14:46,418] Trial 498 finished with value: 0.9600000000000002 and parameters: {'learning_rate': 0.004029660567222199, 'n_estimators': 1764, 'max_depth': 15, 'subsample': 0.6466929904469318, 'colsample_bytree': 0.14608939109031302}. Best is trial 29 with value: 0.968.\n",
            "[I 2023-09-21 17:15:43,142] Trial 499 finished with value: 0.942 and parameters: {'learning_rate': 0.0003593369914674563, 'n_estimators': 1844, 'max_depth': 20, 'subsample': 0.8375913671543963, 'colsample_bytree': 0.7180001729899463}. Best is trial 29 with value: 0.968.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "XGB best parameters:  {'learning_rate': 0.04074652544112853, 'n_estimators': 454, 'max_depth': 8, 'subsample': 0.3153099125619524, 'colsample_bytree': 0.1593272485470127}\n"
          ]
        }
      ],
      "source": [
        "run_optimization('xgb', Iran_train_data, 500)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "aYDk4ZfpBHi6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e4633ce5-8944-4ad5-9b7b-7f5e23f1bef6"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[I 2023-09-21 17:15:43,167] A new study created in memory with name: no-name-82ac1f8f-f9c5-4711-a05f-9441d3842fbf\n",
            "[I 2023-09-21 17:18:02,068] Trial 0 finished with value: 0.954 and parameters: {'learning_rate': 9.096453170325128e-05, 'n_estimators': 2275, 'max_depth': 9, 'subsample': 0.985637059432807, 'colsample_bytree': 0.8529797413035486}. Best is trial 0 with value: 0.954.\n",
            "[I 2023-09-21 17:18:30,842] Trial 1 finished with value: 0.922 and parameters: {'learning_rate': 0.0001437112485585751, 'n_estimators': 2524, 'max_depth': 44, 'subsample': 0.17784845249232692, 'colsample_bytree': 0.7559449110449329}. Best is trial 0 with value: 0.954.\n",
            "[I 2023-09-21 17:18:53,691] Trial 2 finished with value: 0.958 and parameters: {'learning_rate': 0.00029020227713015225, 'n_estimators': 592, 'max_depth': 10, 'subsample': 0.7052607998187295, 'colsample_bytree': 0.655008027729967}. Best is trial 2 with value: 0.958.\n",
            "[I 2023-09-21 17:18:59,247] Trial 3 finished with value: 0.9200000000000002 and parameters: {'learning_rate': 0.00018074299921669773, 'n_estimators': 813, 'max_depth': 31, 'subsample': 0.2056970577734683, 'colsample_bytree': 0.32936560608979715}. Best is trial 2 with value: 0.958.\n",
            "[I 2023-09-21 17:19:13,297] Trial 4 finished with value: 0.93 and parameters: {'learning_rate': 0.0005253261139843954, 'n_estimators': 734, 'max_depth': 33, 'subsample': 0.25699163189487434, 'colsample_bytree': 0.8869937694371318}. Best is trial 2 with value: 0.958.\n",
            "[I 2023-09-21 17:19:34,683] Trial 5 finished with value: 0.974 and parameters: {'learning_rate': 0.037245594179438624, 'n_estimators': 2032, 'max_depth': 6, 'subsample': 0.9435688302330777, 'colsample_bytree': 0.8385388342847484}. Best is trial 5 with value: 0.974.\n",
            "[I 2023-09-21 17:19:48,796] Trial 6 finished with value: 0.9719999999999999 and parameters: {'learning_rate': 0.009522559736940796, 'n_estimators': 363, 'max_depth': 9, 'subsample': 0.541118000924445, 'colsample_bytree': 0.9762140082651098}. Best is trial 5 with value: 0.974.\n",
            "[I 2023-09-21 17:20:01,208] Trial 7 finished with value: 0.9400000000000001 and parameters: {'learning_rate': 0.0010941276726736584, 'n_estimators': 923, 'max_depth': 6, 'subsample': 0.26862475420433385, 'colsample_bytree': 0.48139858933163293}. Best is trial 5 with value: 0.974.\n",
            "[I 2023-09-21 17:20:11,880] Trial 8 finished with value: 0.914 and parameters: {'learning_rate': 1.6727601292004673e-05, 'n_estimators': 1331, 'max_depth': 9, 'subsample': 0.21166585935941296, 'colsample_bytree': 0.400028266259116}. Best is trial 5 with value: 0.974.\n",
            "[I 2023-09-21 17:20:17,320] Trial 9 finished with value: 0.944 and parameters: {'learning_rate': 6.176490110576338e-05, 'n_estimators': 250, 'max_depth': 23, 'subsample': 0.3997058261190439, 'colsample_bytree': 0.37047878464575235}. Best is trial 5 with value: 0.974.\n",
            "[I 2023-09-21 17:20:29,735] Trial 10 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.07203169362124201, 'n_estimators': 2991, 'max_depth': 5, 'subsample': 0.9931403500166204, 'colsample_bytree': 0.11598104308879664}. Best is trial 10 with value: 0.9799999999999999.\n",
            "[I 2023-09-21 17:20:41,861] Trial 11 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.07500205558897576, 'n_estimators': 2888, 'max_depth': 5, 'subsample': 0.9538425458965164, 'colsample_bytree': 0.11207678496256289}. Best is trial 11 with value: 0.9800000000000001.\n",
            "[I 2023-09-21 17:20:56,819] Trial 12 finished with value: 0.978 and parameters: {'learning_rate': 0.09152280759440423, 'n_estimators': 2962, 'max_depth': 5, 'subsample': 0.8213481131616254, 'colsample_bytree': 0.20097582861388474}. Best is trial 11 with value: 0.9800000000000001.\n",
            "[I 2023-09-21 17:21:14,730] Trial 13 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.013519027853173304, 'n_estimators': 2942, 'max_depth': 5, 'subsample': 0.8435346928140175, 'colsample_bytree': 0.1542327576348243}. Best is trial 11 with value: 0.9800000000000001.\n",
            "[I 2023-09-21 17:21:24,712] Trial 14 finished with value: 0.978 and parameters: {'learning_rate': 0.09988713768842969, 'n_estimators': 1789, 'max_depth': 15, 'subsample': 0.9722832381899618, 'colsample_bytree': 0.10323249807368481}. Best is trial 11 with value: 0.9800000000000001.\n",
            "[I 2023-09-21 17:21:57,063] Trial 15 finished with value: 0.976 and parameters: {'learning_rate': 0.003444060502970892, 'n_estimators': 2566, 'max_depth': 7, 'subsample': 0.7302580042464466, 'colsample_bytree': 0.2549054092617729}. Best is trial 11 with value: 0.9800000000000001.\n",
            "[I 2023-09-21 17:22:03,682] Trial 16 finished with value: 0.978 and parameters: {'learning_rate': 0.025032206334634377, 'n_estimators': 1396, 'max_depth': 5, 'subsample': 0.8588653422361239, 'colsample_bytree': 0.10858975115661919}. Best is trial 11 with value: 0.9800000000000001.\n",
            "[I 2023-09-21 17:22:32,853] Trial 17 finished with value: 0.978 and parameters: {'learning_rate': 0.004444494216897076, 'n_estimators': 2614, 'max_depth': 14, 'subsample': 0.6602757988162742, 'colsample_bytree': 0.2544420473240397}. Best is trial 11 with value: 0.9800000000000001.\n",
            "[I 2023-09-21 17:22:49,593] Trial 18 finished with value: 0.978 and parameters: {'learning_rate': 0.042592430936294286, 'n_estimators': 2066, 'max_depth': 7, 'subsample': 0.8874237389599794, 'colsample_bytree': 0.5195099980660904}. Best is trial 11 with value: 0.9800000000000001.\n",
            "[I 2023-09-21 17:23:09,427] Trial 19 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.014910714644192542, 'n_estimators': 2831, 'max_depth': 11, 'subsample': 0.9951750394681979, 'colsample_bytree': 0.2257432709399499}. Best is trial 11 with value: 0.9800000000000001.\n",
            "[I 2023-09-21 17:23:24,186] Trial 20 finished with value: 0.978 and parameters: {'learning_rate': 0.049384831322995044, 'n_estimators': 2411, 'max_depth': 7, 'subsample': 0.7695445531303042, 'colsample_bytree': 0.29026591118393386}. Best is trial 11 with value: 0.9800000000000001.\n",
            "[I 2023-09-21 17:23:42,417] Trial 21 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.01543592828762637, 'n_estimators': 2957, 'max_depth': 5, 'subsample': 0.8862697176585187, 'colsample_bytree': 0.17720454806026137}. Best is trial 11 with value: 0.9800000000000001.\n",
            "[I 2023-09-21 17:23:55,951] Trial 22 finished with value: 0.982 and parameters: {'learning_rate': 0.0870697597717752, 'n_estimators': 2717, 'max_depth': 5, 'subsample': 0.8099903607214713, 'colsample_bytree': 0.14952686022673656}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:24:09,197] Trial 23 finished with value: 0.978 and parameters: {'learning_rate': 0.09361920466408127, 'n_estimators': 2771, 'max_depth': 6, 'subsample': 0.9073551797884579, 'colsample_bytree': 0.10712888244935354}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:24:22,861] Trial 24 finished with value: 0.978 and parameters: {'learning_rate': 0.029763439821991415, 'n_estimators': 2244, 'max_depth': 8, 'subsample': 0.7988971578361961, 'colsample_bytree': 0.1899012692367111}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:24:31,597] Trial 25 finished with value: 0.978 and parameters: {'learning_rate': 0.05573206878499698, 'n_estimators': 1703, 'max_depth': 5, 'subsample': 0.9207924698880163, 'colsample_bytree': 0.3058923218354951}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:24:47,403] Trial 26 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.02495609690464373, 'n_estimators': 2689, 'max_depth': 12, 'subsample': 0.9999554270809256, 'colsample_bytree': 0.16837330371004688}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:25:17,151] Trial 27 finished with value: 0.9739999999999999 and parameters: {'learning_rate': 0.004749457939070519, 'n_estimators': 1154, 'max_depth': 6, 'subsample': 0.9132483081711139, 'colsample_bytree': 0.4280972972210899}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:25:31,366] Trial 28 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.05064926374618909, 'n_estimators': 2333, 'max_depth': 8, 'subsample': 0.8028200066875937, 'colsample_bytree': 0.24540558508298976}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:25:58,752] Trial 29 finished with value: 0.978 and parameters: {'learning_rate': 0.008112247957579083, 'n_estimators': 2126, 'max_depth': 12, 'subsample': 0.9503562399636117, 'colsample_bytree': 0.34678966482210877}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:26:12,699] Trial 30 finished with value: 0.978 and parameters: {'learning_rate': 0.02024910601517249, 'n_estimators': 1820, 'max_depth': 19, 'subsample': 0.9994435715712147, 'colsample_bytree': 0.2655240504399232}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:26:27,049] Trial 31 finished with value: 0.982 and parameters: {'learning_rate': 0.0688666033969385, 'n_estimators': 2999, 'max_depth': 5, 'subsample': 0.8505834711641981, 'colsample_bytree': 0.16260900182187113}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:26:40,907] Trial 32 finished with value: 0.982 and parameters: {'learning_rate': 0.06649919902841686, 'n_estimators': 2754, 'max_depth': 6, 'subsample': 0.858945695842635, 'colsample_bytree': 0.14678551798721914}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:26:55,023] Trial 33 finished with value: 0.978 and parameters: {'learning_rate': 0.03895233834007148, 'n_estimators': 2525, 'max_depth': 6, 'subsample': 0.8502512789883061, 'colsample_bytree': 0.16952361780303515}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:27:10,364] Trial 34 finished with value: 0.978 and parameters: {'learning_rate': 0.09611826832417264, 'n_estimators': 2759, 'max_depth': 8, 'subsample': 0.7498075833392238, 'colsample_bytree': 0.316355743178469}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:27:23,521] Trial 35 finished with value: 0.982 and parameters: {'learning_rate': 0.0580771411521219, 'n_estimators': 2445, 'max_depth': 10, 'subsample': 0.6903867563784599, 'colsample_bytree': 0.2037207829196427}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:27:36,151] Trial 36 finished with value: 0.978 and parameters: {'learning_rate': 0.029548453145076994, 'n_estimators': 2401, 'max_depth': 10, 'subsample': 0.6799245399955051, 'colsample_bytree': 0.21778087361135653}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:27:57,605] Trial 37 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.056233993367946766, 'n_estimators': 2692, 'max_depth': 7, 'subsample': 0.7155573891851833, 'colsample_bytree': 0.6571755942907624}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:28:10,992] Trial 38 finished with value: 0.978 and parameters: {'learning_rate': 0.033146678807986545, 'n_estimators': 2221, 'max_depth': 10, 'subsample': 0.633153768149123, 'colsample_bytree': 0.29652194971271784}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:28:23,264] Trial 39 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.0183431961700632, 'n_estimators': 1926, 'max_depth': 6, 'subsample': 0.7714125718167063, 'colsample_bytree': 0.2164093719960683}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:28:36,423] Trial 40 finished with value: 0.982 and parameters: {'learning_rate': 0.05540756585668755, 'n_estimators': 2470, 'max_depth': 8, 'subsample': 0.6282836731312198, 'colsample_bytree': 0.15205376974950036}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:28:50,506] Trial 41 finished with value: 0.982 and parameters: {'learning_rate': 0.054753408299384285, 'n_estimators': 2508, 'max_depth': 9, 'subsample': 0.616222085741023, 'colsample_bytree': 0.1537684407155295}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:29:04,464] Trial 42 finished with value: 0.978 and parameters: {'learning_rate': 0.03496217018061017, 'n_estimators': 2457, 'max_depth': 8, 'subsample': 0.6953057723637448, 'colsample_bytree': 0.16083192761544363}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:29:17,968] Trial 43 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.06365031726974046, 'n_estimators': 2645, 'max_depth': 44, 'subsample': 0.5782402996265835, 'colsample_bytree': 0.2130628703453142}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:29:29,550] Trial 44 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.07127638056119018, 'n_estimators': 2799, 'max_depth': 6, 'subsample': 0.7424195365614754, 'colsample_bytree': 0.14265374381325957}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:29:49,194] Trial 45 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.022253616161299863, 'n_estimators': 2253, 'max_depth': 7, 'subsample': 0.8061805944067549, 'colsample_bytree': 0.3591658326241056}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:30:06,069] Trial 46 finished with value: 0.976 and parameters: {'learning_rate': 0.04023080602797354, 'n_estimators': 2845, 'max_depth': 9, 'subsample': 0.8423371953390899, 'colsample_bytree': 0.2778360445518314}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:30:22,833] Trial 47 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.010300654121574259, 'n_estimators': 2666, 'max_depth': 5, 'subsample': 0.7150599029142296, 'colsample_bytree': 0.12891974666250222}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:30:37,180] Trial 48 finished with value: 0.982 and parameters: {'learning_rate': 0.06781529840786082, 'n_estimators': 2999, 'max_depth': 6, 'subsample': 0.7739004083678457, 'colsample_bytree': 0.20724336058781032}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:30:46,093] Trial 49 finished with value: 0.978 and parameters: {'learning_rate': 0.0997696144292301, 'n_estimators': 1644, 'max_depth': 7, 'subsample': 0.5237878181868585, 'colsample_bytree': 0.1392642020710678}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:31:03,207] Trial 50 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.024177419145268594, 'n_estimators': 2558, 'max_depth': 5, 'subsample': 0.858951338911637, 'colsample_bytree': 0.2530776241703295}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:31:14,553] Trial 51 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.05585219441699978, 'n_estimators': 2134, 'max_depth': 9, 'subsample': 0.6552464222768882, 'colsample_bytree': 0.14518488413466119}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:31:24,379] Trial 52 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.04471538568378193, 'n_estimators': 2474, 'max_depth': 48, 'subsample': 0.6053200840591904, 'colsample_bytree': 0.10207198047829649}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:31:37,374] Trial 53 finished with value: 0.978 and parameters: {'learning_rate': 0.07188845976322268, 'n_estimators': 2377, 'max_depth': 10, 'subsample': 0.6960044888475393, 'colsample_bytree': 0.1844249619976445}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:31:52,425] Trial 54 finished with value: 0.978 and parameters: {'learning_rate': 0.03787400181434275, 'n_estimators': 2866, 'max_depth': 11, 'subsample': 0.535155888235342, 'colsample_bytree': 0.1509104418014951}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:31:55,565] Trial 55 finished with value: 0.9780000000000001 and parameters: {'learning_rate': 0.07155942610149887, 'n_estimators': 527, 'max_depth': 8, 'subsample': 0.6217638332879967, 'colsample_bytree': 0.23520298350574725}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:31:56,460] Trial 56 finished with value: 0.966 and parameters: {'learning_rate': 0.028729193855072128, 'n_estimators': 64, 'max_depth': 9, 'subsample': 0.6614719860873082, 'colsample_bytree': 0.17901267540029958}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:32:09,934] Trial 57 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.04979981638201664, 'n_estimators': 2571, 'max_depth': 6, 'subsample': 0.8153674052555839, 'colsample_bytree': 0.13021910370583403}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:32:22,198] Trial 58 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.0180516248453631, 'n_estimators': 2001, 'max_depth': 14, 'subsample': 0.7335530817195592, 'colsample_bytree': 0.10112707340779326}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:32:34,195] Trial 59 finished with value: 0.978 and parameters: {'learning_rate': 0.09949172888621013, 'n_estimators': 2732, 'max_depth': 7, 'subsample': 0.5712224494497833, 'colsample_bytree': 0.2002293802282038}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:32:57,884] Trial 60 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.012407605874777978, 'n_estimators': 2329, 'max_depth': 17, 'subsample': 0.8891640656361806, 'colsample_bytree': 0.3304112174518038}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:33:13,117] Trial 61 finished with value: 0.982 and parameters: {'learning_rate': 0.07081847067927168, 'n_estimators': 2999, 'max_depth': 5, 'subsample': 0.7695612896432132, 'colsample_bytree': 0.19758528941633324}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:33:28,852] Trial 62 finished with value: 0.982 and parameters: {'learning_rate': 0.054735119490324724, 'n_estimators': 2893, 'max_depth': 6, 'subsample': 0.7554086360076239, 'colsample_bytree': 0.23733434280529844}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:33:43,166] Trial 63 finished with value: 0.978 and parameters: {'learning_rate': 0.07341731540627978, 'n_estimators': 2983, 'max_depth': 8, 'subsample': 0.7866786632437472, 'colsample_bytree': 0.16670079224996526}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:34:00,372] Trial 64 finished with value: 0.978 and parameters: {'learning_rate': 0.040820725915231115, 'n_estimators': 2884, 'max_depth': 5, 'subsample': 0.821498532028339, 'colsample_bytree': 0.2914781617721886}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:34:15,619] Trial 65 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.025554301205244052, 'n_estimators': 2602, 'max_depth': 6, 'subsample': 0.9350490840835987, 'colsample_bytree': 0.19478481898043415}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:34:26,403] Trial 66 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.0779583717806133, 'n_estimators': 2746, 'max_depth': 7, 'subsample': 0.7866879325006729, 'colsample_bytree': 0.12999594015489013}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:34:35,501] Trial 67 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.04788638143470204, 'n_estimators': 1029, 'max_depth': 12, 'subsample': 0.7344020907430927, 'colsample_bytree': 0.26059909596264785}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:34:49,191] Trial 68 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.06021048422973845, 'n_estimators': 2493, 'max_depth': 5, 'subsample': 0.8634365056932379, 'colsample_bytree': 0.21136655798887277}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:35:04,948] Trial 69 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.031519196546035244, 'n_estimators': 2802, 'max_depth': 6, 'subsample': 0.8307276394884603, 'colsample_bytree': 0.231527109758377}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:35:21,567] Trial 70 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.015712307631811744, 'n_estimators': 2642, 'max_depth': 8, 'subsample': 0.8783901960757177, 'colsample_bytree': 0.16367635905891992}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:35:35,359] Trial 71 finished with value: 0.978 and parameters: {'learning_rate': 0.07964245224914294, 'n_estimators': 2995, 'max_depth': 5, 'subsample': 0.7789460837510643, 'colsample_bytree': 0.2105306206409309}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:35:49,024] Trial 72 finished with value: 0.982 and parameters: {'learning_rate': 0.06225654620520441, 'n_estimators': 2922, 'max_depth': 5, 'subsample': 0.7108125992923199, 'colsample_bytree': 0.18681722185016436}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:36:03,461] Trial 73 finished with value: 0.978 and parameters: {'learning_rate': 0.036437170646795226, 'n_estimators': 2822, 'max_depth': 6, 'subsample': 0.7553722897714925, 'colsample_bytree': 0.12793747890726603}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:36:18,504] Trial 74 finished with value: 0.978 and parameters: {'learning_rate': 0.08588034822671087, 'n_estimators': 2729, 'max_depth': 23, 'subsample': 0.8338577845783415, 'colsample_bytree': 0.27213306951633187}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:36:33,654] Trial 75 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.04486708893651784, 'n_estimators': 2934, 'max_depth': 7, 'subsample': 0.8024146251171054, 'colsample_bytree': 0.15563736653981114}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:36:48,982] Trial 76 finished with value: 0.9780000000000001 and parameters: {'learning_rate': 0.06067261552118152, 'n_estimators': 2452, 'max_depth': 5, 'subsample': 0.684253021119352, 'colsample_bytree': 0.19218386866979595}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:37:07,405] Trial 77 finished with value: 0.9780000000000001 and parameters: {'learning_rate': 0.09893795416604508, 'n_estimators': 2992, 'max_depth': 9, 'subsample': 0.9050430168315652, 'colsample_bytree': 0.11996496402441148}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:37:18,919] Trial 78 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.022257161245375016, 'n_estimators': 1441, 'max_depth': 7, 'subsample': 0.7721127953467506, 'colsample_bytree': 0.23397362365386692}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:37:31,966] Trial 79 finished with value: 0.982 and parameters: {'learning_rate': 0.03125692967746796, 'n_estimators': 2657, 'max_depth': 6, 'subsample': 0.7146208143615603, 'colsample_bytree': 0.17029726256963698}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:37:45,874] Trial 80 finished with value: 0.978 and parameters: {'learning_rate': 0.04919629672663675, 'n_estimators': 2327, 'max_depth': 10, 'subsample': 0.7558259791130725, 'colsample_bytree': 0.31165108275467274}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:38:01,543] Trial 81 finished with value: 0.978 and parameters: {'learning_rate': 0.0585590326068831, 'n_estimators': 2865, 'max_depth': 6, 'subsample': 0.8178038019877658, 'colsample_bytree': 0.24434951415750022}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:38:16,622] Trial 82 finished with value: 0.978 and parameters: {'learning_rate': 0.0741528973623027, 'n_estimators': 2897, 'max_depth': 5, 'subsample': 0.7567326540174089, 'colsample_bytree': 0.21788391584353922}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:38:31,153] Trial 83 finished with value: 0.982 and parameters: {'learning_rate': 0.04136350322605796, 'n_estimators': 2772, 'max_depth': 11, 'subsample': 0.7911415339839956, 'colsample_bytree': 0.1451119949910999}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:38:45,120] Trial 84 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.05683385198832976, 'n_estimators': 2542, 'max_depth': 6, 'subsample': 0.8443677856169399, 'colsample_bytree': 0.19937604491397615}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:38:59,713] Trial 85 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.07633701815110266, 'n_estimators': 2709, 'max_depth': 5, 'subsample': 0.7325894145488188, 'colsample_bytree': 0.26900034585234356}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:39:12,477] Trial 86 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.029359153486989416, 'n_estimators': 2827, 'max_depth': 8, 'subsample': 0.6729236388142288, 'colsample_bytree': 0.11615030587809427}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:39:26,060] Trial 87 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.0489226312202896, 'n_estimators': 2906, 'max_depth': 13, 'subsample': 0.6436357433964881, 'colsample_bytree': 0.17989771431495638}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:39:41,100] Trial 88 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.03492578758257694, 'n_estimators': 2603, 'max_depth': 9, 'subsample': 0.6746316130987704, 'colsample_bytree': 0.2315756803332969}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:39:57,484] Trial 89 finished with value: 0.982 and parameters: {'learning_rate': 0.021525785238279742, 'n_estimators': 2937, 'max_depth': 7, 'subsample': 0.7669699586312039, 'colsample_bytree': 0.15458393549737004}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:40:10,186] Trial 90 finished with value: 0.976 and parameters: {'learning_rate': 0.08347015952411707, 'n_estimators': 2199, 'max_depth': 6, 'subsample': 0.7057035961269305, 'colsample_bytree': 0.24638125542932554}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:40:25,425] Trial 91 finished with value: 0.982 and parameters: {'learning_rate': 0.05883719993199992, 'n_estimators': 2929, 'max_depth': 5, 'subsample': 0.6982230340354023, 'colsample_bytree': 0.1856523347788141}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:40:40,126] Trial 92 finished with value: 0.982 and parameters: {'learning_rate': 0.06513996100151938, 'n_estimators': 2996, 'max_depth': 5, 'subsample': 0.7397502577143469, 'colsample_bytree': 0.13644298971020988}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:40:53,933] Trial 93 finished with value: 0.978 and parameters: {'learning_rate': 0.09960337456368992, 'n_estimators': 2828, 'max_depth': 10, 'subsample': 0.7137247496769812, 'colsample_bytree': 0.18827590500123997}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:41:06,907] Trial 94 finished with value: 0.978 and parameters: {'learning_rate': 0.04422955765309428, 'n_estimators': 2706, 'max_depth': 5, 'subsample': 0.6237481693048799, 'colsample_bytree': 0.20745184355410812}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:41:19,819] Trial 95 finished with value: 0.982 and parameters: {'learning_rate': 0.0635360949557862, 'n_estimators': 2782, 'max_depth': 6, 'subsample': 0.8056976743071927, 'colsample_bytree': 0.1682943744575597}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:41:33,756] Trial 96 finished with value: 0.978 and parameters: {'learning_rate': 0.05005059920913849, 'n_estimators': 2886, 'max_depth': 6, 'subsample': 0.6496813779517013, 'colsample_bytree': 0.10306480477936072}. Best is trial 22 with value: 0.982.\n",
            "[I 2023-09-21 17:41:47,518] Trial 97 finished with value: 0.984 and parameters: {'learning_rate': 0.03715547309484834, 'n_estimators': 2529, 'max_depth': 7, 'subsample': 0.8646850677612571, 'colsample_bytree': 0.1453916995501207}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:42:01,238] Trial 98 finished with value: 0.984 and parameters: {'learning_rate': 0.03555589422032685, 'n_estimators': 2513, 'max_depth': 8, 'subsample': 0.8747489465611686, 'colsample_bytree': 0.14357480214352886}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:42:13,205] Trial 99 finished with value: 0.978 and parameters: {'learning_rate': 0.02600655312019296, 'n_estimators': 2446, 'max_depth': 8, 'subsample': 0.8759214901875904, 'colsample_bytree': 0.1196696400262782}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:42:25,228] Trial 100 finished with value: 0.982 and parameters: {'learning_rate': 0.03484765048711434, 'n_estimators': 2540, 'max_depth': 8, 'subsample': 0.8479915568872639, 'colsample_bytree': 0.14606759262926683}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:42:37,804] Trial 101 finished with value: 0.982 and parameters: {'learning_rate': 0.08292847136081254, 'n_estimators': 2357, 'max_depth': 7, 'subsample': 0.830631264934927, 'colsample_bytree': 0.16276995224936186}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:42:50,287] Trial 102 finished with value: 0.982 and parameters: {'learning_rate': 0.039422267649092534, 'n_estimators': 2276, 'max_depth': 11, 'subsample': 0.900072679888461, 'colsample_bytree': 0.12934577447237372}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:43:03,536] Trial 103 finished with value: 0.978 and parameters: {'learning_rate': 0.06929549947133347, 'n_estimators': 2621, 'max_depth': 9, 'subsample': 0.9351476664868598, 'colsample_bytree': 0.22425731648279848}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:43:13,470] Trial 104 finished with value: 0.982 and parameters: {'learning_rate': 0.08608780623584808, 'n_estimators': 2393, 'max_depth': 34, 'subsample': 0.8687013881827794, 'colsample_bytree': 0.1501984341701414}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:43:28,033] Trial 105 finished with value: 0.978 and parameters: {'learning_rate': 0.05329090832153306, 'n_estimators': 2673, 'max_depth': 7, 'subsample': 0.8582606482525243, 'colsample_bytree': 0.2030467130136442}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:43:33,252] Trial 106 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.04207559247542526, 'n_estimators': 736, 'max_depth': 9, 'subsample': 0.9667790353423696, 'colsample_bytree': 0.16777420579227303}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:43:44,882] Trial 107 finished with value: 0.978 and parameters: {'learning_rate': 0.026532795762984694, 'n_estimators': 2144, 'max_depth': 15, 'subsample': 0.9188502693832603, 'colsample_bytree': 0.1204679267548476}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:44:00,738] Trial 108 finished with value: 0.978 and parameters: {'learning_rate': 0.033758765873476954, 'n_estimators': 2521, 'max_depth': 7, 'subsample': 0.7844668372420044, 'colsample_bytree': 0.28480949160389474}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:44:13,536] Trial 109 finished with value: 0.982 and parameters: {'learning_rate': 0.06841930302000564, 'n_estimators': 2586, 'max_depth': 10, 'subsample': 0.817105750703972, 'colsample_bytree': 0.10038301334981717}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:44:21,271] Trial 110 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.019584733608257205, 'n_estimators': 1211, 'max_depth': 8, 'subsample': 0.8877810871502777, 'colsample_bytree': 0.17975396474007224}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:44:35,995] Trial 111 finished with value: 0.982 and parameters: {'learning_rate': 0.05105389166892049, 'n_estimators': 2747, 'max_depth': 5, 'subsample': 0.7961083675891584, 'colsample_bytree': 0.1880966017827254}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:44:50,161] Trial 112 finished with value: 0.984 and parameters: {'learning_rate': 0.06651672627368431, 'n_estimators': 2854, 'max_depth': 6, 'subsample': 0.8409158485475545, 'colsample_bytree': 0.14298410133853584}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:45:04,227] Trial 113 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.08015521661053084, 'n_estimators': 2842, 'max_depth': 16, 'subsample': 0.8399093600497448, 'colsample_bytree': 0.15668297479111437}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:45:17,169] Trial 114 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.09994986575668964, 'n_estimators': 2674, 'max_depth': 6, 'subsample': 0.8574724645703524, 'colsample_bytree': 0.14020202839332507}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:45:31,633] Trial 115 finished with value: 0.978 and parameters: {'learning_rate': 0.04384343165468695, 'n_estimators': 2787, 'max_depth': 7, 'subsample': 0.8957108006271864, 'colsample_bytree': 0.21840075974110779}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:45:41,739] Trial 116 finished with value: 0.984 and parameters: {'learning_rate': 0.06522683539358738, 'n_estimators': 2496, 'max_depth': 6, 'subsample': 0.8252444784859893, 'colsample_bytree': 0.1341363790386751}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:45:54,349] Trial 117 finished with value: 0.982 and parameters: {'learning_rate': 0.06872621332847383, 'n_estimators': 2480, 'max_depth': 19, 'subsample': 0.8710017108156068, 'colsample_bytree': 0.11732205135188076}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:46:06,616] Trial 118 finished with value: 0.978 and parameters: {'learning_rate': 0.08211858503517142, 'n_estimators': 2417, 'max_depth': 6, 'subsample': 0.822896711026187, 'colsample_bytree': 0.13250222040957557}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:46:18,462] Trial 119 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.029691870224731236, 'n_estimators': 2272, 'max_depth': 9, 'subsample': 0.8382827885527482, 'colsample_bytree': 0.17129637235164544}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:46:30,392] Trial 120 finished with value: 0.982 and parameters: {'learning_rate': 0.05848326569006427, 'n_estimators': 2571, 'max_depth': 8, 'subsample': 0.8021217931523371, 'colsample_bytree': 0.14475632560357263}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:46:46,065] Trial 121 finished with value: 0.984 and parameters: {'learning_rate': 0.05273879884005449, 'n_estimators': 2955, 'max_depth': 6, 'subsample': 0.7712669629963166, 'colsample_bytree': 0.20423460759398596}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:47:02,180] Trial 122 finished with value: 0.978 and parameters: {'learning_rate': 0.03855222635207743, 'n_estimators': 2944, 'max_depth': 7, 'subsample': 0.7799711360576993, 'colsample_bytree': 0.20483537501190338}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:47:15,986] Trial 123 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.04813655994432294, 'n_estimators': 2501, 'max_depth': 12, 'subsample': 0.8770555018199238, 'colsample_bytree': 0.1617806473995978}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:47:30,107] Trial 124 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.08227267847005997, 'n_estimators': 2992, 'max_depth': 6, 'subsample': 0.8514269063217825, 'colsample_bytree': 0.11659055133253238}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:47:43,514] Trial 125 finished with value: 0.982 and parameters: {'learning_rate': 0.06479373874849277, 'n_estimators': 2632, 'max_depth': 13, 'subsample': 0.7656159008594998, 'colsample_bytree': 0.20004498774362753}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:47:55,119] Trial 126 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.05296550480971513, 'n_estimators': 2728, 'max_depth': 8, 'subsample': 0.8144394102827295, 'colsample_bytree': 0.1398724483550543}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:48:10,220] Trial 127 finished with value: 0.976 and parameters: {'learning_rate': 0.07212467575541903, 'n_estimators': 2849, 'max_depth': 6, 'subsample': 0.8298918577926171, 'colsample_bytree': 0.2595863745427499}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:48:24,384] Trial 128 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.03429033387834629, 'n_estimators': 2790, 'max_depth': 5, 'subsample': 0.9100313147196306, 'colsample_bytree': 0.1002498710740759}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:48:40,033] Trial 129 finished with value: 0.982 and parameters: {'learning_rate': 0.042185672623052756, 'n_estimators': 2920, 'max_depth': 7, 'subsample': 0.7404579393029769, 'colsample_bytree': 0.18078122224599907}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:48:53,424] Trial 130 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.05826621548173063, 'n_estimators': 2335, 'max_depth': 6, 'subsample': 0.7943958204647487, 'colsample_bytree': 0.22742773514122644}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:49:08,033] Trial 131 finished with value: 0.982 and parameters: {'learning_rate': 0.05248721467704174, 'n_estimators': 2878, 'max_depth': 6, 'subsample': 0.7693447358782722, 'colsample_bytree': 0.15651569072076466}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:49:23,069] Trial 132 finished with value: 0.978 and parameters: {'learning_rate': 0.08425966719990005, 'n_estimators': 2934, 'max_depth': 5, 'subsample': 0.748424207188838, 'colsample_bytree': 0.2468594096860829}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:49:36,740] Trial 133 finished with value: 0.982 and parameters: {'learning_rate': 0.06009970350101844, 'n_estimators': 2992, 'max_depth': 7, 'subsample': 0.7291298098119057, 'colsample_bytree': 0.17587378301733014}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:49:50,171] Trial 134 finished with value: 0.978 and parameters: {'learning_rate': 0.04410999535483255, 'n_estimators': 2749, 'max_depth': 6, 'subsample': 0.8094051603228788, 'colsample_bytree': 0.19753148587695132}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:50:19,461] Trial 135 finished with value: 0.976 and parameters: {'learning_rate': 0.0020836710940478915, 'n_estimators': 2682, 'max_depth': 7, 'subsample': 0.8597477056154466, 'colsample_bytree': 0.13304127395599494}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:50:36,082] Trial 136 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.028987038271844814, 'n_estimators': 2865, 'max_depth': 5, 'subsample': 0.607329848371085, 'colsample_bytree': 0.22092057409153096}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:50:48,708] Trial 137 finished with value: 0.982 and parameters: {'learning_rate': 0.09958446686864465, 'n_estimators': 2433, 'max_depth': 10, 'subsample': 0.7755810262517078, 'colsample_bytree': 0.15238962534446246}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:51:04,120] Trial 138 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.06701849894333216, 'n_estimators': 2814, 'max_depth': 9, 'subsample': 0.6914483227565866, 'colsample_bytree': 0.23783245072601086}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:51:22,324] Trial 139 finished with value: 0.978 and parameters: {'learning_rate': 0.036366944578829184, 'n_estimators': 2603, 'max_depth': 11, 'subsample': 0.8850751501230871, 'colsample_bytree': 0.40618707234511714}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:51:36,207] Trial 140 finished with value: 0.982 and parameters: {'learning_rate': 0.049791513733666797, 'n_estimators': 2541, 'max_depth': 28, 'subsample': 0.7589164886078066, 'colsample_bytree': 0.1820390283157099}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:51:50,760] Trial 141 finished with value: 0.978 and parameters: {'learning_rate': 0.06303959673852431, 'n_estimators': 2906, 'max_depth': 5, 'subsample': 0.7172765518671214, 'colsample_bytree': 0.1925400570539694}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:52:03,779] Trial 142 finished with value: 0.976 and parameters: {'learning_rate': 0.07421714931299496, 'n_estimators': 2999, 'max_depth': 6, 'subsample': 0.6539822097721593, 'colsample_bytree': 0.16578126218123201}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:52:17,444] Trial 143 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.056976182461734325, 'n_estimators': 2915, 'max_depth': 5, 'subsample': 0.674347122298546, 'colsample_bytree': 0.2090909562748911}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:52:26,717] Trial 144 finished with value: 0.978 and parameters: {'learning_rate': 0.08781199282490544, 'n_estimators': 1560, 'max_depth': 8, 'subsample': 0.8294761152271126, 'colsample_bytree': 0.12514964523385763}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:52:41,000] Trial 145 finished with value: 0.982 and parameters: {'learning_rate': 0.04599754895241744, 'n_estimators': 2820, 'max_depth': 6, 'subsample': 0.756286151570207, 'colsample_bytree': 0.14085518813043707}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:52:57,525] Trial 146 finished with value: 0.978 and parameters: {'learning_rate': 0.02324236344548438, 'n_estimators': 2942, 'max_depth': 17, 'subsample': 0.789308803921382, 'colsample_bytree': 0.18168513358969973}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:53:08,836] Trial 147 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.0696723253962071, 'n_estimators': 2757, 'max_depth': 5, 'subsample': 0.6996722955714194, 'colsample_bytree': 0.11665433822741467}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:53:21,874] Trial 148 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.03878561211888665, 'n_estimators': 2693, 'max_depth': 14, 'subsample': 0.8083133802757971, 'colsample_bytree': 0.1579429300769079}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:53:37,341] Trial 149 finished with value: 0.978 and parameters: {'learning_rate': 0.05386867323594533, 'n_estimators': 2876, 'max_depth': 8, 'subsample': 0.7244005180827345, 'colsample_bytree': 0.21783435938251916}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:53:53,051] Trial 150 finished with value: 0.978 and parameters: {'learning_rate': 0.03310796833394395, 'n_estimators': 2498, 'max_depth': 5, 'subsample': 0.8534503452215729, 'colsample_bytree': 0.2729759862879607}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:54:07,646] Trial 151 finished with value: 0.982 and parameters: {'learning_rate': 0.030272619012938227, 'n_estimators': 2592, 'max_depth': 6, 'subsample': 0.7101172779070768, 'colsample_bytree': 0.1771257064879743}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:54:24,536] Trial 152 finished with value: 0.978 and parameters: {'learning_rate': 0.016783180959019747, 'n_estimators': 2640, 'max_depth': 6, 'subsample': 0.7376830611759123, 'colsample_bytree': 0.19514242770736356}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:54:35,181] Trial 153 finished with value: 0.978 and parameters: {'learning_rate': 0.06494238555916106, 'n_estimators': 1830, 'max_depth': 7, 'subsample': 0.677471858253188, 'colsample_bytree': 0.16696476208134003}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:54:45,685] Trial 154 finished with value: 0.982 and parameters: {'learning_rate': 0.08479318775028201, 'n_estimators': 2660, 'max_depth': 48, 'subsample': 0.7221833759002924, 'colsample_bytree': 0.14392879740974246}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:54:59,205] Trial 155 finished with value: 0.978 and parameters: {'learning_rate': 0.04395300278398979, 'n_estimators': 2395, 'max_depth': 6, 'subsample': 0.7760264547058332, 'colsample_bytree': 0.2353573735732152}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:55:33,560] Trial 156 finished with value: 0.978 and parameters: {'learning_rate': 0.008197662387377149, 'n_estimators': 2944, 'max_depth': 9, 'subsample': 0.6281430451548244, 'colsample_bytree': 0.4958814811051211}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:55:49,919] Trial 157 finished with value: 0.978 and parameters: {'learning_rate': 0.013606466518552185, 'n_estimators': 2817, 'max_depth': 19, 'subsample': 0.6632795297473455, 'colsample_bytree': 0.12528804950994504}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:56:03,753] Trial 158 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.05346871120966553, 'n_estimators': 2470, 'max_depth': 7, 'subsample': 0.8399722246007492, 'colsample_bytree': 0.20097096633073025}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:56:18,998] Trial 159 finished with value: 0.982 and parameters: {'learning_rate': 0.026623498240672575, 'n_estimators': 2710, 'max_depth': 5, 'subsample': 0.7467843077257013, 'colsample_bytree': 0.15762485869904627}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:56:33,406] Trial 160 finished with value: 0.978 and parameters: {'learning_rate': 0.07032432901162654, 'n_estimators': 2762, 'max_depth': 13, 'subsample': 0.6872882216869318, 'colsample_bytree': 0.18401787280946963}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:56:48,248] Trial 161 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.03742187518944883, 'n_estimators': 2868, 'max_depth': 11, 'subsample': 0.7913617516906418, 'colsample_bytree': 0.144095166462869}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:57:01,166] Trial 162 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.04234654105870533, 'n_estimators': 2779, 'max_depth': 10, 'subsample': 0.8211204792450594, 'colsample_bytree': 0.13801951785146668}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:57:11,997] Trial 163 finished with value: 0.978 and parameters: {'learning_rate': 0.09984038979159687, 'n_estimators': 2541, 'max_depth': 10, 'subsample': 0.7656295009420561, 'colsample_bytree': 0.1684479235442215}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:57:26,181] Trial 164 finished with value: 0.978 and parameters: {'learning_rate': 0.05900410673157323, 'n_estimators': 2945, 'max_depth': 9, 'subsample': 0.8024936811680398, 'colsample_bytree': 0.1113999070170875}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:57:40,731] Trial 165 finished with value: 0.978 and parameters: {'learning_rate': 0.04914731199626191, 'n_estimators': 2869, 'max_depth': 6, 'subsample': 0.8375878296902541, 'colsample_bytree': 0.15280249003535995}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:58:10,886] Trial 166 finished with value: 0.9739999999999999 and parameters: {'learning_rate': 0.0006066028984487716, 'n_estimators': 2705, 'max_depth': 11, 'subsample': 0.866534057637578, 'colsample_bytree': 0.10208731165744207}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:58:28,815] Trial 167 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.08013554093796398, 'n_estimators': 2624, 'max_depth': 8, 'subsample': 0.5862856626109691, 'colsample_bytree': 0.5656502959055588}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:58:32,669] Trial 168 finished with value: 0.978 and parameters: {'learning_rate': 0.03279178483559454, 'n_estimators': 472, 'max_depth': 12, 'subsample': 0.7880214093183133, 'colsample_bytree': 0.2125195859301374}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:58:49,752] Trial 169 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.019250546789097902, 'n_estimators': 2986, 'max_depth': 6, 'subsample': 0.6421535460123603, 'colsample_bytree': 0.17256595731456423}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:59:04,120] Trial 170 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.042361868560274955, 'n_estimators': 2849, 'max_depth': 5, 'subsample': 0.7005533228419508, 'colsample_bytree': 0.12664239238136726}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:59:18,818] Trial 171 finished with value: 0.982 and parameters: {'learning_rate': 0.06302674897195171, 'n_estimators': 2930, 'max_depth': 7, 'subsample': 0.7541766562666532, 'colsample_bytree': 0.1507637579657314}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:59:33,688] Trial 172 finished with value: 0.982 and parameters: {'learning_rate': 0.05123431191457945, 'n_estimators': 2802, 'max_depth': 6, 'subsample': 0.772706385506342, 'colsample_bytree': 0.1955544256504296}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 17:59:49,632] Trial 173 finished with value: 0.982 and parameters: {'learning_rate': 0.024147719705512636, 'n_estimators': 2897, 'max_depth': 7, 'subsample': 0.7247119084441461, 'colsample_bytree': 0.16468101442471228}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:00:03,341] Trial 174 finished with value: 0.982 and parameters: {'learning_rate': 0.03724841193612809, 'n_estimators': 2757, 'max_depth': 9, 'subsample': 0.8116041653952474, 'colsample_bytree': 0.13594954529625397}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:00:18,255] Trial 175 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.07804454342716773, 'n_estimators': 2994, 'max_depth': 8, 'subsample': 0.7499685613083626, 'colsample_bytree': 0.25250744209781206}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:00:31,591] Trial 176 finished with value: 0.978 and parameters: {'learning_rate': 0.030003912259202566, 'n_estimators': 2562, 'max_depth': 11, 'subsample': 0.7921520757563908, 'colsample_bytree': 0.18622207551013645}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:00:47,343] Trial 177 finished with value: 0.978 and parameters: {'learning_rate': 0.021845709836527415, 'n_estimators': 2918, 'max_depth': 7, 'subsample': 0.5526789331325677, 'colsample_bytree': 0.15345075949100337}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:01:02,683] Trial 178 finished with value: 0.978 and parameters: {'learning_rate': 0.06159766169283463, 'n_estimators': 2433, 'max_depth': 30, 'subsample': 0.8945990814725298, 'colsample_bytree': 0.35706599979059794}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:01:19,758] Trial 179 finished with value: 0.978 and parameters: {'learning_rate': 0.04570028586151569, 'n_estimators': 2834, 'max_depth': 8, 'subsample': 0.766899212868557, 'colsample_bytree': 0.3061728102785837}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:01:27,827] Trial 180 finished with value: 0.978 and parameters: {'learning_rate': 0.07138562453987396, 'n_estimators': 953, 'max_depth': 20, 'subsample': 0.8757060427552739, 'colsample_bytree': 0.2128495163463058}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:01:42,020] Trial 181 finished with value: 0.982 and parameters: {'learning_rate': 0.05723305147632845, 'n_estimators': 2951, 'max_depth': 5, 'subsample': 0.7177389171481329, 'colsample_bytree': 0.17617024729155845}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:01:56,080] Trial 182 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.053680430338323315, 'n_estimators': 2996, 'max_depth': 5, 'subsample': 0.698054512988333, 'colsample_bytree': 0.19041788301747747}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:02:09,482] Trial 183 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.03824896152056653, 'n_estimators': 2905, 'max_depth': 35, 'subsample': 0.6549340662329277, 'colsample_bytree': 0.12272201976800365}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:02:23,208] Trial 184 finished with value: 0.978 and parameters: {'learning_rate': 0.08568446367222511, 'n_estimators': 2501, 'max_depth': 5, 'subsample': 0.7375473043722631, 'colsample_bytree': 0.22764313538882458}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:02:37,312] Trial 185 finished with value: 0.982 and parameters: {'learning_rate': 0.06666320795336178, 'n_estimators': 2808, 'max_depth': 6, 'subsample': 0.7061252715133286, 'colsample_bytree': 0.14719651115948665}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:02:51,676] Trial 186 finished with value: 0.982 and parameters: {'learning_rate': 0.04604405394261387, 'n_estimators': 2654, 'max_depth': 40, 'subsample': 0.8259633347825145, 'colsample_bytree': 0.17071789557154868}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:03:06,751] Trial 187 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.05901889942624923, 'n_estimators': 2887, 'max_depth': 6, 'subsample': 0.8477738453235092, 'colsample_bytree': 0.1967369364527143}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:03:21,292] Trial 188 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.03337412835553731, 'n_estimators': 2943, 'max_depth': 27, 'subsample': 0.6348186653765542, 'colsample_bytree': 0.13401931434333988}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:03:38,460] Trial 189 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.011970955243525067, 'n_estimators': 2739, 'max_depth': 10, 'subsample': 0.6725664969684708, 'colsample_bytree': 0.1601476865497898}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:03:48,292] Trial 190 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.07425340544326087, 'n_estimators': 2377, 'max_depth': 24, 'subsample': 0.7853211553865453, 'colsample_bytree': 0.1804163331571174}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:04:05,227] Trial 191 finished with value: 0.982 and parameters: {'learning_rate': 0.06434423370936815, 'n_estimators': 2990, 'max_depth': 5, 'subsample': 0.737029256576825, 'colsample_bytree': 0.33305871047105506}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:04:29,987] Trial 192 finished with value: 0.978 and parameters: {'learning_rate': 0.004575472751643781, 'n_estimators': 2926, 'max_depth': 5, 'subsample': 0.7510549913838142, 'colsample_bytree': 0.1394327949901521}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:04:42,472] Trial 193 finished with value: 0.9780000000000001 and parameters: {'learning_rate': 0.08698343936473338, 'n_estimators': 2856, 'max_depth': 5, 'subsample': 0.7248206410997875, 'colsample_bytree': 0.12095660967521799}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:04:55,300] Trial 194 finished with value: 0.982 and parameters: {'learning_rate': 0.04993484080557775, 'n_estimators': 2950, 'max_depth': 17, 'subsample': 0.6854564008539757, 'colsample_bytree': 0.15122167186327173}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:05:23,561] Trial 195 finished with value: 0.96 and parameters: {'learning_rate': 0.00014833651666036832, 'n_estimators': 2799, 'max_depth': 6, 'subsample': 0.6136450394672308, 'colsample_bytree': 0.11326206766261365}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:05:38,389] Trial 196 finished with value: 0.982 and parameters: {'learning_rate': 0.07205540030747203, 'n_estimators': 2989, 'max_depth': 5, 'subsample': 0.763670325386089, 'colsample_bytree': 0.1666995094973596}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:05:54,448] Trial 197 finished with value: 0.978 and parameters: {'learning_rate': 0.04179839968199709, 'n_estimators': 3000, 'max_depth': 6, 'subsample': 0.8020118574864751, 'colsample_bytree': 0.19785529936445562}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:06:08,090] Trial 198 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.09918864088761649, 'n_estimators': 2866, 'max_depth': 14, 'subsample': 0.7084130134174883, 'colsample_bytree': 0.13748929879256544}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:06:20,337] Trial 199 finished with value: 0.982 and parameters: {'learning_rate': 0.05722045766392194, 'n_estimators': 2594, 'max_depth': 9, 'subsample': 0.7376758259416525, 'colsample_bytree': 0.21682379302802063}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:06:38,249] Trial 200 finished with value: 0.982 and parameters: {'learning_rate': 0.04924934517242916, 'n_estimators': 2899, 'max_depth': 7, 'subsample': 0.5998635108841187, 'colsample_bytree': 0.3820177553788405}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:06:50,190] Trial 201 finished with value: 0.982 and parameters: {'learning_rate': 0.06670691692211593, 'n_estimators': 2785, 'max_depth': 6, 'subsample': 0.8193144043262579, 'colsample_bytree': 0.17164390891184514}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:07:04,173] Trial 202 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.060808780824391596, 'n_estimators': 2711, 'max_depth': 7, 'subsample': 0.8082789265415017, 'colsample_bytree': 0.15606046672793963}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:07:18,829] Trial 203 finished with value: 0.978 and parameters: {'learning_rate': 0.07941987259994872, 'n_estimators': 2836, 'max_depth': 13, 'subsample': 0.7837963134366887, 'colsample_bytree': 0.18822309534716136}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:07:36,708] Trial 204 finished with value: 0.976 and parameters: {'learning_rate': 0.0406275845935354, 'n_estimators': 2524, 'max_depth': 15, 'subsample': 0.8570421641109304, 'colsample_bytree': 0.4550806175385389}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:08:01,837] Trial 205 finished with value: 0.978 and parameters: {'learning_rate': 0.0030963525135098684, 'n_estimators': 2650, 'max_depth': 6, 'subsample': 0.7735602810762481, 'colsample_bytree': 0.13629288706869702}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:08:14,888] Trial 206 finished with value: 0.982 and parameters: {'learning_rate': 0.05369911990882364, 'n_estimators': 2758, 'max_depth': 5, 'subsample': 0.831169823606448, 'colsample_bytree': 0.17448272580158972}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:08:28,873] Trial 207 finished with value: 0.978 and parameters: {'learning_rate': 0.027063435826783097, 'n_estimators': 2922, 'max_depth': 8, 'subsample': 0.8005567141111395, 'colsample_bytree': 0.10453349800113995}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:08:42,321] Trial 208 finished with value: 0.976 and parameters: {'learning_rate': 0.0687863758955338, 'n_estimators': 2437, 'max_depth': 6, 'subsample': 0.7508108231204111, 'colsample_bytree': 0.20659700274722068}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:08:56,546] Trial 209 finished with value: 0.982 and parameters: {'learning_rate': 0.0856683144975071, 'n_estimators': 2875, 'max_depth': 6, 'subsample': 0.8460859876984126, 'colsample_bytree': 0.1562117009970322}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:09:13,111] Trial 210 finished with value: 0.978 and parameters: {'learning_rate': 0.04592492845521411, 'n_estimators': 2944, 'max_depth': 12, 'subsample': 0.8811421710643247, 'colsample_bytree': 0.24458404782733004}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:09:26,456] Trial 211 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.03553318299126629, 'n_estimators': 2536, 'max_depth': 9, 'subsample': 0.4992796757430481, 'colsample_bytree': 0.14387302588830433}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:09:39,372] Trial 212 finished with value: 0.984 and parameters: {'learning_rate': 0.03090056882183953, 'n_estimators': 2471, 'max_depth': 16, 'subsample': 0.8672979826255713, 'colsample_bytree': 0.1642145509497149}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:09:53,808] Trial 213 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.019476595767637567, 'n_estimators': 2464, 'max_depth': 17, 'subsample': 0.8668431486023906, 'colsample_bytree': 0.17619302182265972}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:10:06,849] Trial 214 finished with value: 0.982 and parameters: {'learning_rate': 0.029234675932551194, 'n_estimators': 2589, 'max_depth': 18, 'subsample': 0.9136827139074641, 'colsample_bytree': 0.13124012167387994}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:10:29,190] Trial 215 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.005509370953392221, 'n_estimators': 2320, 'max_depth': 10, 'subsample': 0.8225521853652279, 'colsample_bytree': 0.15920955644460247}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:10:39,972] Trial 216 finished with value: 0.982 and parameters: {'learning_rate': 0.05962416051666841, 'n_estimators': 2480, 'max_depth': 18, 'subsample': 0.7720927803069422, 'colsample_bytree': 0.1865513774810247}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:10:55,372] Trial 217 finished with value: 0.978 and parameters: {'learning_rate': 0.04981790103180532, 'n_estimators': 2702, 'max_depth': 16, 'subsample': 0.8895420602955034, 'colsample_bytree': 0.22517953183361683}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:11:12,300] Trial 218 finished with value: 0.966 and parameters: {'learning_rate': 0.03846261072357307, 'n_estimators': 2999, 'max_depth': 7, 'subsample': 0.12875243937619046, 'colsample_bytree': 0.7312438335903555}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:12:03,937] Trial 219 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 5.3361216486877015e-05, 'n_estimators': 2400, 'max_depth': 12, 'subsample': 0.8495989572546466, 'colsample_bytree': 0.2864520241812719}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:12:17,083] Trial 220 finished with value: 0.9780000000000001 and parameters: {'learning_rate': 0.0730366408658522, 'n_estimators': 2799, 'max_depth': 5, 'subsample': 0.6914610488252887, 'colsample_bytree': 0.12385683899514054}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:12:32,211] Trial 221 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.02363572354057424, 'n_estimators': 2634, 'max_depth': 8, 'subsample': 0.8612863319856072, 'colsample_bytree': 0.14804753464683443}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:12:46,659] Trial 222 finished with value: 0.982 and parameters: {'learning_rate': 0.034134184805113155, 'n_estimators': 2558, 'max_depth': 8, 'subsample': 0.8378356308398123, 'colsample_bytree': 0.16742755117919275}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:12:59,606] Trial 223 finished with value: 0.982 and parameters: {'learning_rate': 0.057067067934934386, 'n_estimators': 2491, 'max_depth': 9, 'subsample': 0.7977484142203357, 'colsample_bytree': 0.1434864704732333}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:13:14,802] Trial 224 finished with value: 0.984 and parameters: {'learning_rate': 0.0441564893755605, 'n_estimators': 2902, 'max_depth': 8, 'subsample': 0.7227460282383392, 'colsample_bytree': 0.19838802751875292}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:13:29,152] Trial 225 finished with value: 0.984 and parameters: {'learning_rate': 0.0424314736765875, 'n_estimators': 2900, 'max_depth': 16, 'subsample': 0.71843884564054, 'colsample_bytree': 0.20047666380302726}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:13:43,403] Trial 226 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.048161799123125695, 'n_estimators': 2913, 'max_depth': 16, 'subsample': 0.714084509362127, 'colsample_bytree': 0.20541332977141172}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:13:58,299] Trial 227 finished with value: 0.982 and parameters: {'learning_rate': 0.04224525199431223, 'n_estimators': 2942, 'max_depth': 15, 'subsample': 0.729230400123685, 'colsample_bytree': 0.19275012397037447}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:14:14,553] Trial 228 finished with value: 0.978 and parameters: {'learning_rate': 0.03231372124025555, 'n_estimators': 2857, 'max_depth': 16, 'subsample': 0.6627387420182076, 'colsample_bytree': 0.22387859501629287}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:14:30,863] Trial 229 finished with value: 0.982 and parameters: {'learning_rate': 0.040259121796883915, 'n_estimators': 2890, 'max_depth': 15, 'subsample': 0.6990919362819681, 'colsample_bytree': 0.2576687452278507}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:15:12,616] Trial 230 finished with value: 0.974 and parameters: {'learning_rate': 0.0013430977368651836, 'n_estimators': 2960, 'max_depth': 14, 'subsample': 0.7400211680865951, 'colsample_bytree': 0.20624697007686213}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:15:27,048] Trial 231 finished with value: 0.978 and parameters: {'learning_rate': 0.0665183954707239, 'n_estimators': 2807, 'max_depth': 11, 'subsample': 0.7187085808589345, 'colsample_bytree': 0.18083293484068144}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:15:41,087] Trial 232 finished with value: 0.982 and parameters: {'learning_rate': 0.05461146714618577, 'n_estimators': 2849, 'max_depth': 16, 'subsample': 0.6837822511449027, 'colsample_bytree': 0.1641285095648972}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:15:53,910] Trial 233 finished with value: 0.982 and parameters: {'learning_rate': 0.06440826012522118, 'n_estimators': 2898, 'max_depth': 16, 'subsample': 0.75704808367167, 'colsample_bytree': 0.18587442830137885}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:16:06,773] Trial 234 finished with value: 0.982 and parameters: {'learning_rate': 0.0849385110820895, 'n_estimators': 2765, 'max_depth': 21, 'subsample': 0.7401440452378474, 'colsample_bytree': 0.1606154870001378}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:16:34,967] Trial 235 finished with value: 0.978 and parameters: {'learning_rate': 0.04669435944037818, 'n_estimators': 2949, 'max_depth': 10, 'subsample': 0.7778741985865386, 'colsample_bytree': 0.8922406426362377}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:16:48,164] Trial 236 finished with value: 0.978 and parameters: {'learning_rate': 0.01111333972494993, 'n_estimators': 1967, 'max_depth': 8, 'subsample': 0.6461154247093945, 'colsample_bytree': 0.12126033880637736}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:17:04,618] Trial 237 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.027761474493267914, 'n_estimators': 3000, 'max_depth': 22, 'subsample': 0.715989899798454, 'colsample_bytree': 0.20294001287645436}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:17:19,107] Trial 238 finished with value: 0.982 and parameters: {'learning_rate': 0.05731482885324576, 'n_estimators': 2826, 'max_depth': 7, 'subsample': 0.7630828181771331, 'colsample_bytree': 0.23853524308151186}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:17:30,322] Trial 239 finished with value: 0.978 and parameters: {'learning_rate': 0.0750625605159315, 'n_estimators': 2905, 'max_depth': 6, 'subsample': 0.2977207757062355, 'colsample_bytree': 0.1703561425799242}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:17:46,348] Trial 240 finished with value: 0.982 and parameters: {'learning_rate': 0.016129135019188112, 'n_estimators': 2717, 'max_depth': 15, 'subsample': 0.7048927688830751, 'colsample_bytree': 0.14878717723696486}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:18:00,305] Trial 241 finished with value: 0.984 and parameters: {'learning_rate': 0.03169719093350619, 'n_estimators': 2533, 'max_depth': 8, 'subsample': 0.8812417385796992, 'colsample_bytree': 0.1415708886774565}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:18:13,463] Trial 242 finished with value: 0.984 and parameters: {'learning_rate': 0.037922351962851465, 'n_estimators': 2426, 'max_depth': 9, 'subsample': 0.8717083311803558, 'colsample_bytree': 0.12939304067710672}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:18:26,332] Trial 243 finished with value: 0.984 and parameters: {'learning_rate': 0.030508293332386957, 'n_estimators': 2438, 'max_depth': 9, 'subsample': 0.8709207739365808, 'colsample_bytree': 0.13489790943284777}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:18:37,001] Trial 244 finished with value: 0.978 and parameters: {'learning_rate': 0.024220917280557516, 'n_estimators': 2426, 'max_depth': 9, 'subsample': 0.8986940015685856, 'colsample_bytree': 0.11333536720128796}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:18:50,676] Trial 245 finished with value: 0.982 and parameters: {'learning_rate': 0.033914678195931254, 'n_estimators': 2511, 'max_depth': 9, 'subsample': 0.877521794233889, 'colsample_bytree': 0.1341107305809906}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:19:03,403] Trial 246 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.02979315378892819, 'n_estimators': 2337, 'max_depth': 8, 'subsample': 0.8724915083554472, 'colsample_bytree': 0.10149219637381526}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:19:15,954] Trial 247 finished with value: 0.982 and parameters: {'learning_rate': 0.038483921949686306, 'n_estimators': 2382, 'max_depth': 9, 'subsample': 0.9059153789581418, 'colsample_bytree': 0.12954719271119908}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:19:28,451] Trial 248 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.022899272293961603, 'n_estimators': 2454, 'max_depth': 10, 'subsample': 0.887263928767958, 'colsample_bytree': 0.15017801900717728}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:19:41,214] Trial 249 finished with value: 0.978 and parameters: {'learning_rate': 0.029502390426536466, 'n_estimators': 2292, 'max_depth': 8, 'subsample': 0.8544082523072423, 'colsample_bytree': 0.18563934246083358}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:19:55,175] Trial 250 finished with value: 0.982 and parameters: {'learning_rate': 0.04211285932679182, 'n_estimators': 2536, 'max_depth': 9, 'subsample': 0.9257261328352877, 'colsample_bytree': 0.15713280096323978}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:21:26,287] Trial 251 finished with value: 0.9639999999999999 and parameters: {'learning_rate': 0.0003497196855856335, 'n_estimators': 2464, 'max_depth': 36, 'subsample': 0.8700664200460589, 'colsample_bytree': 0.532194862540765}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:21:43,862] Trial 252 finished with value: 0.978 and parameters: {'learning_rate': 0.03456928163736805, 'n_estimators': 2363, 'max_depth': 8, 'subsample': 0.8417395987534037, 'colsample_bytree': 0.4257548044214823}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:22:28,107] Trial 253 finished with value: 0.978 and parameters: {'learning_rate': 0.006702760720575091, 'n_estimators': 2601, 'max_depth': 43, 'subsample': 0.8961826619634771, 'colsample_bytree': 0.5782062677026355}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:22:49,809] Trial 254 finished with value: 0.978 and parameters: {'learning_rate': 0.019051472176067733, 'n_estimators': 2511, 'max_depth': 13, 'subsample': 0.8647798076267034, 'colsample_bytree': 0.3179081822608414}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:23:07,229] Trial 255 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.014208950877733365, 'n_estimators': 2560, 'max_depth': 9, 'subsample': 0.6806384956913101, 'colsample_bytree': 0.21563595349300624}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:23:16,804] Trial 256 finished with value: 0.978 and parameters: {'learning_rate': 0.047336143808462544, 'n_estimators': 2410, 'max_depth': 25, 'subsample': 0.9552322408091678, 'colsample_bytree': 0.12458164982419573}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:23:31,061] Trial 257 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.027153358375271584, 'n_estimators': 2454, 'max_depth': 10, 'subsample': 0.6187020349441775, 'colsample_bytree': 0.17647229112453724}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:23:45,186] Trial 258 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.035312488608260854, 'n_estimators': 2658, 'max_depth': 14, 'subsample': 0.8266120087305184, 'colsample_bytree': 0.14125423418937416}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:23:52,679] Trial 259 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.049936097973537354, 'n_estimators': 1333, 'max_depth': 17, 'subsample': 0.5988449618008139, 'colsample_bytree': 0.19250318135036362}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:24:11,844] Trial 260 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.01045377119263478, 'n_estimators': 2564, 'max_depth': 8, 'subsample': 0.8835151086067362, 'colsample_bytree': 0.16256034191957108}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:24:22,611] Trial 261 finished with value: 0.978 and parameters: {'learning_rate': 0.03859868495723754, 'n_estimators': 2237, 'max_depth': 7, 'subsample': 0.564834709117563, 'colsample_bytree': 0.23200894056180824}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:24:35,178] Trial 262 finished with value: 0.984 and parameters: {'learning_rate': 0.05447512122656084, 'n_estimators': 2407, 'max_depth': 20, 'subsample': 0.851835599774468, 'colsample_bytree': 0.1471750376132988}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:24:47,937] Trial 263 finished with value: 0.982 and parameters: {'learning_rate': 0.043581184229172426, 'n_estimators': 2423, 'max_depth': 20, 'subsample': 0.8547327473717239, 'colsample_bytree': 0.11324706304240445}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:25:01,578] Trial 264 finished with value: 0.978 and parameters: {'learning_rate': 0.021261295214772297, 'n_estimators': 2364, 'max_depth': 19, 'subsample': 0.840839430691016, 'colsample_bytree': 0.13536006297597986}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:25:16,588] Trial 265 finished with value: 0.9780000000000001 and parameters: {'learning_rate': 0.05478258526476048, 'n_estimators': 2468, 'max_depth': 22, 'subsample': 0.8668313721086551, 'colsample_bytree': 0.3908657154106746}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:25:28,725] Trial 266 finished with value: 0.978 and parameters: {'learning_rate': 0.02620737579795254, 'n_estimators': 2505, 'max_depth': 23, 'subsample': 0.8182896732010551, 'colsample_bytree': 0.14628167952565121}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:25:44,461] Trial 267 finished with value: 0.978 and parameters: {'learning_rate': 0.032275438659552284, 'n_estimators': 2515, 'max_depth': 20, 'subsample': 0.9322344229856842, 'colsample_bytree': 0.2688978268119845}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:25:46,613] Trial 268 finished with value: 0.9719999999999999 and parameters: {'learning_rate': 0.07407105495676834, 'n_estimators': 114, 'max_depth': 11, 'subsample': 0.9024831873728257, 'colsample_bytree': 0.12456142406935536}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:25:58,971] Trial 269 finished with value: 0.982 and parameters: {'learning_rate': 0.047022711249684, 'n_estimators': 2594, 'max_depth': 16, 'subsample': 0.8421934041455565, 'colsample_bytree': 0.1673138679206869}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:26:13,560] Trial 270 finished with value: 0.978 and parameters: {'learning_rate': 0.09089057464411006, 'n_estimators': 2403, 'max_depth': 17, 'subsample': 0.7892496336896424, 'colsample_bytree': 0.3683754227709331}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:26:27,068] Trial 271 finished with value: 0.982 and parameters: {'learning_rate': 0.06223939187147615, 'n_estimators': 2638, 'max_depth': 19, 'subsample': 0.8749029046168296, 'colsample_bytree': 0.15100345049098107}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:26:42,511] Trial 272 finished with value: 0.978 and parameters: {'learning_rate': 0.04239385524288057, 'n_estimators': 2862, 'max_depth': 21, 'subsample': 0.8111362752863474, 'colsample_bytree': 0.20115657232846518}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:26:53,558] Trial 273 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.05625806433485095, 'n_estimators': 2293, 'max_depth': 8, 'subsample': 0.855629311233502, 'colsample_bytree': 0.17394818040044174}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:27:12,949] Trial 274 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.016695744963995177, 'n_estimators': 2458, 'max_depth': 18, 'subsample': 0.5855061239559858, 'colsample_bytree': 0.3325498694053505}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:27:21,424] Trial 275 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.03601014974016962, 'n_estimators': 2059, 'max_depth': 30, 'subsample': 0.757416438495713, 'colsample_bytree': 0.11753713598464202}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:28:43,154] Trial 276 finished with value: 0.968 and parameters: {'learning_rate': 0.0007672832371719547, 'n_estimators': 2685, 'max_depth': 26, 'subsample': 0.8310336395374505, 'colsample_bytree': 0.46502942403035386}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:29:08,561] Trial 277 finished with value: 0.976 and parameters: {'learning_rate': 0.0019118744832550632, 'n_estimators': 2937, 'max_depth': 23, 'subsample': 0.66756147022286, 'colsample_bytree': 0.10013231828392305}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:29:19,638] Trial 278 finished with value: 0.982 and parameters: {'learning_rate': 0.0760569105120612, 'n_estimators': 2755, 'max_depth': 15, 'subsample': 0.9144252160183793, 'colsample_bytree': 0.13819898562664718}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:29:33,059] Trial 279 finished with value: 0.982 and parameters: {'learning_rate': 0.031183839505242016, 'n_estimators': 2558, 'max_depth': 13, 'subsample': 0.8878769056799033, 'colsample_bytree': 0.16143024265485145}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:29:46,245] Trial 280 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.049903102408669305, 'n_estimators': 2358, 'max_depth': 10, 'subsample': 0.7279780518360963, 'colsample_bytree': 0.19090165139187268}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:30:02,275] Trial 281 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.06253252942563733, 'n_estimators': 2854, 'max_depth': 17, 'subsample': 0.6264811464913331, 'colsample_bytree': 0.29235940008505656}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:30:17,536] Trial 282 finished with value: 0.978 and parameters: {'learning_rate': 0.09731815417455829, 'n_estimators': 3000, 'max_depth': 7, 'subsample': 0.7836002205284761, 'colsample_bytree': 0.21450579333611156}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:30:30,925] Trial 283 finished with value: 0.982 and parameters: {'learning_rate': 0.042440869113170035, 'n_estimators': 2489, 'max_depth': 9, 'subsample': 0.8069162709818106, 'colsample_bytree': 0.1500730772107568}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:30:40,002] Trial 284 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.024848896492864835, 'n_estimators': 1720, 'max_depth': 14, 'subsample': 0.8604678249742694, 'colsample_bytree': 0.17746345538071331}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:30:53,967] Trial 285 finished with value: 0.978 and parameters: {'learning_rate': 0.06580527141127385, 'n_estimators': 2806, 'max_depth': 6, 'subsample': 0.5371656866519731, 'colsample_bytree': 0.12263547529591386}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:31:11,341] Trial 286 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.05216759945454813, 'n_estimators': 2930, 'max_depth': 12, 'subsample': 0.7558860026776774, 'colsample_bytree': 0.3395411109385987}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:32:00,790] Trial 287 finished with value: 0.9639999999999999 and parameters: {'learning_rate': 1.1946435493870277e-05, 'n_estimators': 2602, 'max_depth': 18, 'subsample': 0.8290712812238478, 'colsample_bytree': 0.24308324770949602}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:32:15,727] Trial 288 finished with value: 0.978 and parameters: {'learning_rate': 0.03797681409076746, 'n_estimators': 2885, 'max_depth': 20, 'subsample': 0.5190549861704469, 'colsample_bytree': 0.13380966496001476}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:32:28,420] Trial 289 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.08323281219843118, 'n_estimators': 2392, 'max_depth': 9, 'subsample': 0.7390575289165792, 'colsample_bytree': 0.15818603056850655}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:32:44,913] Trial 290 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.031671490894151715, 'n_estimators': 2950, 'max_depth': 15, 'subsample': 0.8791061490742168, 'colsample_bytree': 0.19752449522616466}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:33:07,263] Trial 291 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.006395701777353157, 'n_estimators': 2729, 'max_depth': 47, 'subsample': 0.6443795845296403, 'colsample_bytree': 0.21954409682969783}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:33:20,987] Trial 292 finished with value: 0.982 and parameters: {'learning_rate': 0.05332996475643181, 'n_estimators': 2518, 'max_depth': 8, 'subsample': 0.776103109157198, 'colsample_bytree': 0.17980593848890092}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:33:36,188] Trial 293 finished with value: 0.976 and parameters: {'learning_rate': 0.07082257182512433, 'n_estimators': 2450, 'max_depth': 30, 'subsample': 0.8467044304616246, 'colsample_bytree': 0.3671562286574894}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:33:50,204] Trial 294 finished with value: 0.982 and parameters: {'learning_rate': 0.0435696289881282, 'n_estimators': 2657, 'max_depth': 7, 'subsample': 0.7941387317912071, 'colsample_bytree': 0.14737090635073338}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:34:05,509] Trial 295 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.027703027154421182, 'n_estimators': 2837, 'max_depth': 32, 'subsample': 0.6935376328184116, 'colsample_bytree': 0.1666586604064344}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:34:20,789] Trial 296 finished with value: 0.978 and parameters: {'learning_rate': 0.020707877365836895, 'n_estimators': 2772, 'max_depth': 16, 'subsample': 0.9863895469248393, 'colsample_bytree': 0.1354596015068326}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:34:41,816] Trial 297 finished with value: 0.978 and parameters: {'learning_rate': 0.059880836411999754, 'n_estimators': 2893, 'max_depth': 18, 'subsample': 0.7159371973706592, 'colsample_bytree': 0.6659303080606311}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:34:55,383] Trial 298 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.03856871042217553, 'n_estimators': 2567, 'max_depth': 28, 'subsample': 0.8971745597487908, 'colsample_bytree': 0.11630077408934436}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:35:15,158] Trial 299 finished with value: 0.978 and parameters: {'learning_rate': 0.07784993538532642, 'n_estimators': 2183, 'max_depth': 6, 'subsample': 0.8665577425037363, 'colsample_bytree': 0.9888363838667102}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:35:30,843] Trial 300 finished with value: 0.978 and parameters: {'learning_rate': 0.04830289658458746, 'n_estimators': 2948, 'max_depth': 10, 'subsample': 0.8184791496958994, 'colsample_bytree': 0.2039533462964536}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:35:44,932] Trial 301 finished with value: 0.978 and parameters: {'learning_rate': 0.032348206912271256, 'n_estimators': 2440, 'max_depth': 8, 'subsample': 0.6607208623099488, 'colsample_bytree': 0.1854231921022764}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:36:16,215] Trial 302 finished with value: 0.9739999999999999 and parameters: {'learning_rate': 0.0035854204218112116, 'n_estimators': 3000, 'max_depth': 11, 'subsample': 0.5680098694893998, 'colsample_bytree': 0.2620226063872352}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:37:06,540] Trial 303 finished with value: 0.966 and parameters: {'learning_rate': 0.0004499282662689677, 'n_estimators': 1886, 'max_depth': 8, 'subsample': 0.7466631577203092, 'colsample_bytree': 0.4189556374865139}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:37:40,676] Trial 304 finished with value: 0.966 and parameters: {'learning_rate': 0.0001761297546369412, 'n_estimators': 1537, 'max_depth': 22, 'subsample': 0.846692729978404, 'colsample_bytree': 0.30693861689879876}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:37:50,706] Trial 305 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.0980256880759674, 'n_estimators': 2342, 'max_depth': 38, 'subsample': 0.7673765689841988, 'colsample_bytree': 0.15114162998386807}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:38:04,653] Trial 306 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.06479327525418867, 'n_estimators': 2825, 'max_depth': 9, 'subsample': 0.6272729083003351, 'colsample_bytree': 0.2319969296302768}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:38:17,939] Trial 307 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.0512596656740396, 'n_estimators': 2694, 'max_depth': 14, 'subsample': 0.7257395210336696, 'colsample_bytree': 0.10096188596490234}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:38:32,769] Trial 308 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.02424610973542276, 'n_estimators': 2520, 'max_depth': 24, 'subsample': 0.7976162441726198, 'colsample_bytree': 0.1686816311307422}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:38:54,773] Trial 309 finished with value: 0.976 and parameters: {'learning_rate': 0.013084311054149112, 'n_estimators': 2616, 'max_depth': 15, 'subsample': 0.7040975537306251, 'colsample_bytree': 0.347432249341707}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:39:09,159] Trial 310 finished with value: 0.982 and parameters: {'learning_rate': 0.0396983507294619, 'n_estimators': 2900, 'max_depth': 21, 'subsample': 0.919171814606814, 'colsample_bytree': 0.13135248202721816}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:39:22,179] Trial 311 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.07529333750313856, 'n_estimators': 2402, 'max_depth': 7, 'subsample': 0.8822759143455005, 'colsample_bytree': 0.18914414791541895}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:40:02,037] Trial 312 finished with value: 0.9639999999999999 and parameters: {'learning_rate': 8.428355300343413e-05, 'n_estimators': 2949, 'max_depth': 6, 'subsample': 0.8326833565952927, 'colsample_bytree': 0.15612536050542344}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:40:43,450] Trial 313 finished with value: 0.962 and parameters: {'learning_rate': 0.00021321461135945222, 'n_estimators': 2750, 'max_depth': 43, 'subsample': 0.6769737238764423, 'colsample_bytree': 0.2037419466905657}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:41:13,554] Trial 314 finished with value: 0.9719999999999999 and parameters: {'learning_rate': 0.0010802664062233055, 'n_estimators': 2491, 'max_depth': 10, 'subsample': 0.7742924430596998, 'colsample_bytree': 0.14214447944906705}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:41:18,789] Trial 315 finished with value: 0.982 and parameters: {'learning_rate': 0.05785331368014883, 'n_estimators': 1081, 'max_depth': 11, 'subsample': 0.8593064851608496, 'colsample_bytree': 0.17342806190617718}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:41:33,009] Trial 316 finished with value: 0.978 and parameters: {'learning_rate': 0.04590923200677432, 'n_estimators': 2849, 'max_depth': 33, 'subsample': 0.8103125654897709, 'colsample_bytree': 0.12018880024048469}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:42:10,973] Trial 317 finished with value: 0.974 and parameters: {'learning_rate': 0.0013543464006276807, 'n_estimators': 2573, 'max_depth': 26, 'subsample': 0.7471413132686289, 'colsample_bytree': 0.21961801178334325}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:42:29,058] Trial 318 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.01592709115351164, 'n_estimators': 3000, 'max_depth': 19, 'subsample': 0.9396302237603312, 'colsample_bytree': 0.16123207146358776}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:42:52,442] Trial 319 finished with value: 0.978 and parameters: {'learning_rate': 0.03546209743704686, 'n_estimators': 2889, 'max_depth': 5, 'subsample': 0.900328697210283, 'colsample_bytree': 0.4946198519673598}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:43:05,590] Trial 320 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.028400408064745277, 'n_estimators': 2791, 'max_depth': 6, 'subsample': 0.606637631838045, 'colsample_bytree': 0.14000675972336357}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:43:33,795] Trial 321 finished with value: 0.978 and parameters: {'learning_rate': 0.002991227440999768, 'n_estimators': 2418, 'max_depth': 9, 'subsample': 0.8704964541104399, 'colsample_bytree': 0.1823875122656763}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:43:48,567] Trial 322 finished with value: 0.976 and parameters: {'learning_rate': 0.06772311634068505, 'n_estimators': 2671, 'max_depth': 18, 'subsample': 0.8400966329635369, 'colsample_bytree': 0.2533337902665647}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:44:06,939] Trial 323 finished with value: 0.976 and parameters: {'learning_rate': 0.00399658894459288, 'n_estimators': 2325, 'max_depth': 24, 'subsample': 0.735361552467515, 'colsample_bytree': 0.11681577994000597}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:44:12,905] Trial 324 finished with value: 0.976 and parameters: {'learning_rate': 0.08159959185952587, 'n_estimators': 712, 'max_depth': 7, 'subsample': 0.6937573392443408, 'colsample_bytree': 0.20304331666413078}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:44:25,625] Trial 325 finished with value: 0.982 and parameters: {'learning_rate': 0.05569348748025086, 'n_estimators': 2919, 'max_depth': 13, 'subsample': 0.7621394624694933, 'colsample_bytree': 0.15604590244781183}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:44:44,640] Trial 326 finished with value: 0.978 and parameters: {'learning_rate': 0.04695760743899532, 'n_estimators': 2551, 'max_depth': 9, 'subsample': 0.4895372440651052, 'colsample_bytree': 0.5892221270895958}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:45:04,121] Trial 327 finished with value: 0.978 and parameters: {'learning_rate': 0.037706143700305325, 'n_estimators': 2461, 'max_depth': 6, 'subsample': 0.6401160994102705, 'colsample_bytree': 0.5392550728611512}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:46:07,001] Trial 328 finished with value: 0.978 and parameters: {'learning_rate': 0.007026833498696804, 'n_estimators': 2819, 'max_depth': 17, 'subsample': 0.7871566882909278, 'colsample_bytree': 0.9535991893800015}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:46:20,594] Trial 329 finished with value: 0.976 and parameters: {'learning_rate': 0.06391657641037748, 'n_estimators': 2623, 'max_depth': 8, 'subsample': 0.8213943110246691, 'colsample_bytree': 0.27446579313926933}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:46:34,432] Trial 330 finished with value: 0.976 and parameters: {'learning_rate': 0.018343978924674154, 'n_estimators': 2734, 'max_depth': 16, 'subsample': 0.24578406649937568, 'colsample_bytree': 0.1325556682154375}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:46:50,455] Trial 331 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.0305795181453839, 'n_estimators': 2940, 'max_depth': 5, 'subsample': 0.5970815057927829, 'colsample_bytree': 0.17702285817964036}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:47:13,834] Trial 332 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.010990131609944548, 'n_estimators': 2872, 'max_depth': 7, 'subsample': 0.8567502642033932, 'colsample_bytree': 0.23638998301950415}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:47:24,544] Trial 333 finished with value: 0.984 and parameters: {'learning_rate': 0.04255093673312915, 'n_estimators': 2260, 'max_depth': 50, 'subsample': 0.7219917576078134, 'colsample_bytree': 0.14669169356869938}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:47:40,938] Trial 334 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.04237730398486744, 'n_estimators': 2232, 'max_depth': 44, 'subsample': 0.7107390521421971, 'colsample_bytree': 0.45813883456788973}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:47:57,598] Trial 335 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.008232057814081952, 'n_estimators': 2286, 'max_depth': 32, 'subsample': 0.7177198209043312, 'colsample_bytree': 0.14643605682082136}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:48:19,982] Trial 336 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.05495402756046488, 'n_estimators': 2368, 'max_depth': 20, 'subsample': 0.6824400321764648, 'colsample_bytree': 0.8291732837285343}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:48:33,962] Trial 337 finished with value: 0.9720000000000001 and parameters: {'learning_rate': 0.08529846539541082, 'n_estimators': 2521, 'max_depth': 41, 'subsample': 0.894173165293781, 'colsample_bytree': 0.3898882879040596}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:48:48,151] Trial 338 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.009692312729969833, 'n_estimators': 2453, 'max_depth': 22, 'subsample': 0.6592124959852799, 'colsample_bytree': 0.10165292865308113}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:49:03,484] Trial 339 finished with value: 0.978 and parameters: {'learning_rate': 0.07133524662789033, 'n_estimators': 2495, 'max_depth': 33, 'subsample': 0.8781118582407329, 'colsample_bytree': 0.35851686561913426}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:49:16,988] Trial 340 finished with value: 0.982 and parameters: {'learning_rate': 0.04879731311118447, 'n_estimators': 2396, 'max_depth': 39, 'subsample': 0.7067083111571445, 'colsample_bytree': 0.1908735944094112}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:49:34,492] Trial 341 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.05937724202252367, 'n_estimators': 2585, 'max_depth': 37, 'subsample': 0.7290033992428301, 'colsample_bytree': 0.5074697772063667}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:49:48,475] Trial 342 finished with value: 0.984 and parameters: {'learning_rate': 0.0414028065130367, 'n_estimators': 2694, 'max_depth': 47, 'subsample': 0.8440473989041555, 'colsample_bytree': 0.1279509657197001}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:50:06,451] Trial 343 finished with value: 0.978 and parameters: {'learning_rate': 0.035621725125929586, 'n_estimators': 2548, 'max_depth': 46, 'subsample': 0.8457718335741106, 'colsample_bytree': 0.4023948643328106}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:50:20,291] Trial 344 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.04489237949206248, 'n_estimators': 2685, 'max_depth': 46, 'subsample': 0.5844146229661887, 'colsample_bytree': 0.12109003035680427}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:50:33,385] Trial 345 finished with value: 0.976 and parameters: {'learning_rate': 0.09623564880007361, 'n_estimators': 2626, 'max_depth': 25, 'subsample': 0.8622997808405615, 'colsample_bytree': 0.2205672706584102}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:50:43,581] Trial 346 finished with value: 0.984 and parameters: {'learning_rate': 0.06996449054556814, 'n_estimators': 2473, 'max_depth': 13, 'subsample': 0.8304723235485549, 'colsample_bytree': 0.13080846858934922}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:50:56,199] Trial 347 finished with value: 0.982 and parameters: {'learning_rate': 0.07571532807367533, 'n_estimators': 2429, 'max_depth': 30, 'subsample': 0.8300881319555904, 'colsample_bytree': 0.12767250545535072}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:51:08,690] Trial 348 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.06270680188825323, 'n_estimators': 2465, 'max_depth': 49, 'subsample': 0.836813098297656, 'colsample_bytree': 0.1122053019972005}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:51:17,738] Trial 349 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.08313864948277754, 'n_estimators': 2378, 'max_depth': 48, 'subsample': 0.8524074988567555, 'colsample_bytree': 0.13651979481953727}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:51:33,451] Trial 350 finished with value: 0.978 and parameters: {'learning_rate': 0.0557670557703826, 'n_estimators': 2297, 'max_depth': 49, 'subsample': 0.8763022717483251, 'colsample_bytree': 0.4443762904934681}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:51:46,379] Trial 351 finished with value: 0.9759999999999998 and parameters: {'learning_rate': 0.0998864612023551, 'n_estimators': 2428, 'max_depth': 12, 'subsample': 0.8195560198155428, 'colsample_bytree': 0.1615241206083551}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:51:59,883] Trial 352 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.06671253790400113, 'n_estimators': 2489, 'max_depth': 13, 'subsample': 0.8041360726448196, 'colsample_bytree': 0.14490631125100822}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:53:01,331] Trial 353 finished with value: 0.9739999999999999 and parameters: {'learning_rate': 0.0020923269731588055, 'n_estimators': 2348, 'max_depth': 36, 'subsample': 0.9145040832270528, 'colsample_bytree': 0.4307841990520921}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:53:12,057] Trial 354 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.05098227498304573, 'n_estimators': 2526, 'max_depth': 33, 'subsample': 0.8466684901401133, 'colsample_bytree': 0.10170106852694898}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:53:24,830] Trial 355 finished with value: 0.982 and parameters: {'learning_rate': 0.07614814310021961, 'n_estimators': 2484, 'max_depth': 49, 'subsample': 0.8854150147491846, 'colsample_bytree': 0.12643789088199187}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:53:43,709] Trial 356 finished with value: 0.978 and parameters: {'learning_rate': 0.04192378072549502, 'n_estimators': 2996, 'max_depth': 49, 'subsample': 0.8612108265087823, 'colsample_bytree': 0.3832790947015037}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:53:55,135] Trial 357 finished with value: 0.976 and parameters: {'learning_rate': 0.06590987109228404, 'n_estimators': 1634, 'max_depth': 14, 'subsample': 0.8291104527941925, 'colsample_bytree': 0.3114631639012736}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:54:11,651] Trial 358 finished with value: 0.978 and parameters: {'learning_rate': 0.055977764477706866, 'n_estimators': 2407, 'max_depth': 46, 'subsample': 0.8726184152012268, 'colsample_bytree': 0.4691204208455746}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:54:56,458] Trial 359 finished with value: 0.9639999999999999 and parameters: {'learning_rate': 0.0003273065810054537, 'n_estimators': 2559, 'max_depth': 43, 'subsample': 0.6344476002939364, 'colsample_bytree': 0.2882138114718801}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:55:07,827] Trial 360 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.045472714998711264, 'n_estimators': 2321, 'max_depth': 36, 'subsample': 0.5512484419600358, 'colsample_bytree': 0.17315883288966818}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:55:54,873] Trial 361 finished with value: 0.968 and parameters: {'learning_rate': 0.0008913414430941106, 'n_estimators': 2945, 'max_depth': 50, 'subsample': 0.8170731093262997, 'colsample_bytree': 0.20473934037834102}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:56:09,166] Trial 362 finished with value: 0.982 and parameters: {'learning_rate': 0.08236602602789639, 'n_estimators': 2880, 'max_depth': 46, 'subsample': 0.8920396580142425, 'colsample_bytree': 0.15701408240425127}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:56:23,395] Trial 363 finished with value: 0.9200000000000002 and parameters: {'learning_rate': 4.111334690128003e-05, 'n_estimators': 2503, 'max_depth': 50, 'subsample': 0.1695011884196242, 'colsample_bytree': 0.12920251497135882}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:56:36,842] Trial 364 finished with value: 0.978 and parameters: {'learning_rate': 0.03718446905844763, 'n_estimators': 2600, 'max_depth': 12, 'subsample': 0.8414989222412022, 'colsample_bytree': 0.18637090723991898}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:56:54,022] Trial 365 finished with value: 0.978 and parameters: {'learning_rate': 0.053060672168607194, 'n_estimators': 2429, 'max_depth': 41, 'subsample': 0.9791721942220772, 'colsample_bytree': 0.48786630382128515}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:57:17,695] Trial 366 finished with value: 0.96 and parameters: {'learning_rate': 0.00022931616513285997, 'n_estimators': 2116, 'max_depth': 28, 'subsample': 0.6726158768415017, 'colsample_bytree': 0.1463999078192027}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:57:32,175] Trial 367 finished with value: 0.982 and parameters: {'learning_rate': 0.0631861492061203, 'n_estimators': 2820, 'max_depth': 23, 'subsample': 0.7461890588119259, 'colsample_bytree': 0.16782349758079262}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:57:44,372] Trial 368 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.02104589831076898, 'n_estimators': 1429, 'max_depth': 29, 'subsample': 0.8608903048102303, 'colsample_bytree': 0.22042323706491096}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:58:26,312] Trial 369 finished with value: 0.978 and parameters: {'learning_rate': 0.005316611716205251, 'n_estimators': 2999, 'max_depth': 39, 'subsample': 0.9103504201111756, 'colsample_bytree': 0.4054634243604306}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:59:23,248] Trial 370 finished with value: 0.9639999999999999 and parameters: {'learning_rate': 2.921358113585262e-05, 'n_estimators': 2910, 'max_depth': 34, 'subsample': 0.8301679531501525, 'colsample_bytree': 0.25239965806634157}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:59:39,920] Trial 371 finished with value: 0.976 and parameters: {'learning_rate': 0.004808875412092716, 'n_estimators': 2386, 'max_depth': 26, 'subsample': 0.6186715116830764, 'colsample_bytree': 0.11575295655358228}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 18:59:56,313] Trial 372 finished with value: 0.978 and parameters: {'learning_rate': 0.07053744974674368, 'n_estimators': 2534, 'max_depth': 31, 'subsample': 0.7933689921782716, 'colsample_bytree': 0.47888893777108965}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:00:05,679] Trial 373 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.02665353621775031, 'n_estimators': 2254, 'max_depth': 44, 'subsample': 0.4213019425052008, 'colsample_bytree': 0.14193561840654906}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:00:20,974] Trial 374 finished with value: 0.9780000000000001 and parameters: {'learning_rate': 0.04775696964523272, 'n_estimators': 2776, 'max_depth': 14, 'subsample': 0.6580065119145214, 'colsample_bytree': 0.19476974628358043}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:00:36,862] Trial 375 finished with value: 0.982 and parameters: {'learning_rate': 0.03358754904209701, 'n_estimators': 2857, 'max_depth': 42, 'subsample': 0.7307205567358626, 'colsample_bytree': 0.16370063181836186}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:00:59,633] Trial 376 finished with value: 0.978 and parameters: {'learning_rate': 0.04316212563919264, 'n_estimators': 2476, 'max_depth': 16, 'subsample': 0.9447966756616737, 'colsample_bytree': 0.622832882963427}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:01:27,739] Trial 377 finished with value: 0.968 and parameters: {'learning_rate': 0.0007055961971123132, 'n_estimators': 2944, 'max_depth': 41, 'subsample': 0.5756771869561313, 'colsample_bytree': 0.13037154815546861}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:01:41,855] Trial 378 finished with value: 0.9739999999999999 and parameters: {'learning_rate': 0.0878591934609884, 'n_estimators': 2593, 'max_depth': 29, 'subsample': 0.8502986553984477, 'colsample_bytree': 0.23810539178220794}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:01:56,121] Trial 379 finished with value: 0.982 and parameters: {'learning_rate': 0.05611490488906871, 'n_estimators': 2703, 'max_depth': 38, 'subsample': 0.6922841348029035, 'colsample_bytree': 0.17824874315365052}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:02:13,125] Trial 380 finished with value: 0.982 and parameters: {'learning_rate': 0.07178903981576501, 'n_estimators': 2425, 'max_depth': 47, 'subsample': 0.9651219563287456, 'colsample_bytree': 0.5427606256461887}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:02:27,328] Trial 381 finished with value: 0.978 and parameters: {'learning_rate': 0.03885648863934916, 'n_estimators': 2352, 'max_depth': 47, 'subsample': 0.812837223333401, 'colsample_bytree': 0.21043337639827048}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:02:43,068] Trial 382 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.03070450784992841, 'n_estimators': 2888, 'max_depth': 35, 'subsample': 0.6055522103497597, 'colsample_bytree': 0.15050082298147577}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:03:51,655] Trial 383 finished with value: 0.966 and parameters: {'learning_rate': 0.0004060170735369852, 'n_estimators': 2949, 'max_depth': 35, 'subsample': 0.7649273736638346, 'colsample_bytree': 0.3447173666696569}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:04:24,303] Trial 384 finished with value: 0.9719999999999999 and parameters: {'learning_rate': 0.00025687425798236364, 'n_estimators': 2645, 'max_depth': 18, 'subsample': 0.8817699196770511, 'colsample_bytree': 0.11985050867865668}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:04:39,718] Trial 385 finished with value: 0.978 and parameters: {'learning_rate': 0.05212537427326033, 'n_estimators': 2510, 'max_depth': 40, 'subsample': 0.8681434710673409, 'colsample_bytree': 0.32035830798815784}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:04:46,846] Trial 386 finished with value: 0.9639999999999999 and parameters: {'learning_rate': 0.003452501986236877, 'n_estimators': 291, 'max_depth': 25, 'subsample': 0.7820207610659022, 'colsample_bytree': 0.44327085623629836}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:06:36,032] Trial 387 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.00010413535857010177, 'n_estimators': 2803, 'max_depth': 50, 'subsample': 0.7474930993190035, 'colsample_bytree': 0.6719324485907447}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:06:55,374] Trial 388 finished with value: 0.976 and parameters: {'learning_rate': 0.06235165956671165, 'n_estimators': 2456, 'max_depth': 27, 'subsample': 0.8061933651094388, 'colsample_bytree': 0.7257656124884615}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:07:07,749] Trial 389 finished with value: 0.984 and parameters: {'learning_rate': 0.09943468935535893, 'n_estimators': 2571, 'max_depth': 45, 'subsample': 0.9020194111562753, 'colsample_bytree': 0.10133655853963854}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:07:17,925] Trial 390 finished with value: 0.982 and parameters: {'learning_rate': 0.08718127098017762, 'n_estimators': 2571, 'max_depth': 45, 'subsample': 0.8948176661675208, 'colsample_bytree': 0.11405477143855977}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:07:32,407] Trial 391 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.012426929154100893, 'n_estimators': 2540, 'max_depth': 44, 'subsample': 0.9207193307199752, 'colsample_bytree': 0.10556322928851283}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:07:45,693] Trial 392 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.0894886204190453, 'n_estimators': 2625, 'max_depth': 50, 'subsample': 0.8423833239695243, 'colsample_bytree': 0.13500150813313042}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:07:58,654] Trial 393 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.075194010414025, 'n_estimators': 2675, 'max_depth': 47, 'subsample': 0.8973001311429437, 'colsample_bytree': 0.10380597399950961}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:08:14,618] Trial 394 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.09717759135189252, 'n_estimators': 2475, 'max_depth': 45, 'subsample': 0.8714358243932203, 'colsample_bytree': 0.5297438991916843}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:08:29,978] Trial 395 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.015688029768502927, 'n_estimators': 2560, 'max_depth': 32, 'subsample': 0.9096032069739535, 'colsample_bytree': 0.13012671349753607}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:08:51,000] Trial 396 finished with value: 0.978 and parameters: {'learning_rate': 0.005716807295839945, 'n_estimators': 2608, 'max_depth': 15, 'subsample': 0.8829262600380631, 'colsample_bytree': 0.1514074503152618}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:09:56,503] Trial 397 finished with value: 0.976 and parameters: {'learning_rate': 0.002592824640177089, 'n_estimators': 2727, 'max_depth': 44, 'subsample': 0.849821028743825, 'colsample_bytree': 0.49876918044122986}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:10:11,662] Trial 398 finished with value: 0.978 and parameters: {'learning_rate': 0.023247514455865995, 'n_estimators': 2512, 'max_depth': 21, 'subsample': 0.9529213540121458, 'colsample_bytree': 0.16511903330255054}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:10:30,950] Trial 399 finished with value: 0.974 and parameters: {'learning_rate': 0.004483303172844966, 'n_estimators': 2363, 'max_depth': 39, 'subsample': 0.9234258893931966, 'colsample_bytree': 0.11764068759907044}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:11:06,725] Trial 400 finished with value: 0.978 and parameters: {'learning_rate': 0.007971456781548158, 'n_estimators': 2432, 'max_depth': 41, 'subsample': 0.826694622371401, 'colsample_bytree': 0.5202368629757929}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:11:19,508] Trial 401 finished with value: 0.978 and parameters: {'learning_rate': 0.0984290851656279, 'n_estimators': 2528, 'max_depth': 17, 'subsample': 0.5592762716882512, 'colsample_bytree': 0.1419202061875158}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:11:26,198] Trial 402 finished with value: 0.976 and parameters: {'learning_rate': 0.03612113324636527, 'n_estimators': 1259, 'max_depth': 34, 'subsample': 0.3659251442096205, 'colsample_bytree': 0.18042179491328036}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:11:38,083] Trial 403 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.046577857961639456, 'n_estimators': 2653, 'max_depth': 12, 'subsample': 0.7994102425634876, 'colsample_bytree': 0.1030587976442627}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:11:53,554] Trial 404 finished with value: 0.978 and parameters: {'learning_rate': 0.07287418055900943, 'n_estimators': 2472, 'max_depth': 38, 'subsample': 0.6495499181451735, 'colsample_bytree': 0.4197592955964684}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:12:06,067] Trial 405 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.057240372047084015, 'n_estimators': 2316, 'max_depth': 10, 'subsample': 0.5933868006240653, 'colsample_bytree': 0.15811510144198887}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:12:25,828] Trial 406 finished with value: 0.978 and parameters: {'learning_rate': 0.013868841984557007, 'n_estimators': 2581, 'max_depth': 43, 'subsample': 0.8620704795678421, 'colsample_bytree': 0.26627753598795567}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:14:01,324] Trial 407 finished with value: 0.966 and parameters: {'learning_rate': 0.00044437793291030156, 'n_estimators': 2734, 'max_depth': 13, 'subsample': 0.8351977186126578, 'colsample_bytree': 0.5157126921397164}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:14:26,963] Trial 408 finished with value: 0.9739999999999999 and parameters: {'learning_rate': 0.0013771904343362648, 'n_estimators': 2402, 'max_depth': 27, 'subsample': 0.7758772739256072, 'colsample_bytree': 0.13118284029030577}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:14:43,161] Trial 409 finished with value: 0.978 and parameters: {'learning_rate': 0.03140547514791082, 'n_estimators': 2508, 'max_depth': 19, 'subsample': 0.902196923630102, 'colsample_bytree': 0.28686542684104854}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:15:26,054] Trial 410 finished with value: 0.976 and parameters: {'learning_rate': 0.008889242750583504, 'n_estimators': 2839, 'max_depth': 11, 'subsample': 0.9983307650962794, 'colsample_bytree': 0.5585495386498075}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:16:12,540] Trial 411 finished with value: 0.966 and parameters: {'learning_rate': 0.00012682921334499284, 'n_estimators': 2441, 'max_depth': 14, 'subsample': 0.8760775953459378, 'colsample_bytree': 0.23166804296497245}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:17:02,795] Trial 412 finished with value: 0.958 and parameters: {'learning_rate': 0.0005592635411101264, 'n_estimators': 2572, 'max_depth': 15, 'subsample': 0.5802528082576127, 'colsample_bytree': 0.368328671003035}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:17:18,823] Trial 413 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.04149650924244531, 'n_estimators': 2999, 'max_depth': 28, 'subsample': 0.9316513429888033, 'colsample_bytree': 0.19531954336011317}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:17:48,406] Trial 414 finished with value: 0.968 and parameters: {'learning_rate': 0.0009680309908028351, 'n_estimators': 2772, 'max_depth': 13, 'subsample': 0.6177694838198701, 'colsample_bytree': 0.1475392504270543}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:18:02,155] Trial 415 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.025822302911815375, 'n_estimators': 2672, 'max_depth': 47, 'subsample': 0.8162806464470076, 'colsample_bytree': 0.17153065661276273}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:18:22,207] Trial 416 finished with value: 0.976 and parameters: {'learning_rate': 0.06621936779115853, 'n_estimators': 2357, 'max_depth': 29, 'subsample': 0.8582647774692277, 'colsample_bytree': 0.7833441371052632}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:18:30,858] Trial 417 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.05062356170767873, 'n_estimators': 2203, 'max_depth': 9, 'subsample': 0.7583898725291434, 'colsample_bytree': 0.11818469705554147}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:18:50,854] Trial 418 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.006948767768860574, 'n_estimators': 2916, 'max_depth': 17, 'subsample': 0.6345248192683693, 'colsample_bytree': 0.13233269451755497}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:19:29,268] Trial 419 finished with value: 0.9639999999999999 and parameters: {'learning_rate': 2.2740697739359253e-05, 'n_estimators': 2494, 'max_depth': 32, 'subsample': 0.7295477573825944, 'colsample_bytree': 0.20958776642091947}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:19:40,802] Trial 420 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.07950009255101109, 'n_estimators': 2601, 'max_depth': 8, 'subsample': 0.841743634835116, 'colsample_bytree': 0.15295121624880043}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:19:58,948] Trial 421 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.061845393469025935, 'n_estimators': 2408, 'max_depth': 25, 'subsample': 0.8853243894727281, 'colsample_bytree': 0.6209348709909579}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:20:12,804] Trial 422 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.04045568715255962, 'n_estimators': 2824, 'max_depth': 23, 'subsample': 0.8583377397156926, 'colsample_bytree': 0.19010174050408374}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:20:20,414] Trial 423 finished with value: 0.96 and parameters: {'learning_rate': 0.00017228083506257743, 'n_estimators': 844, 'max_depth': 16, 'subsample': 0.5432946209220268, 'colsample_bytree': 0.10135917764440097}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:20:46,200] Trial 424 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.004380248143845698, 'n_estimators': 2956, 'max_depth': 37, 'subsample': 0.7901236497406553, 'colsample_bytree': 0.162274375051336}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:20:58,637] Trial 425 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.05248687398954625, 'n_estimators': 2884, 'max_depth': 20, 'subsample': 0.6922338750574486, 'colsample_bytree': 0.1418153147959471}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:21:13,587] Trial 426 finished with value: 0.976 and parameters: {'learning_rate': 0.019221805048535302, 'n_estimators': 2533, 'max_depth': 22, 'subsample': 0.5199202256559387, 'colsample_bytree': 0.17303873872511433}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:21:28,429] Trial 427 finished with value: 0.978 and parameters: {'learning_rate': 0.034166596138010964, 'n_estimators': 2466, 'max_depth': 45, 'subsample': 0.8174733250839891, 'colsample_bytree': 0.222183359159677}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:21:52,454] Trial 428 finished with value: 0.976 and parameters: {'learning_rate': 0.0028059659642396036, 'n_estimators': 2735, 'max_depth': 14, 'subsample': 0.7154775706635501, 'colsample_bytree': 0.12141113915340224}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:22:03,089] Trial 429 finished with value: 0.978 and parameters: {'learning_rate': 0.09932522902377507, 'n_estimators': 2287, 'max_depth': 42, 'subsample': 0.7633777152585635, 'colsample_bytree': 0.2490394667632764}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:22:29,617] Trial 430 finished with value: 0.976 and parameters: {'learning_rate': 0.002193114641906871, 'n_estimators': 2636, 'max_depth': 15, 'subsample': 0.6663878483629473, 'colsample_bytree': 0.13707504962974956}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:22:44,561] Trial 431 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.07755813906974436, 'n_estimators': 2997, 'max_depth': 11, 'subsample': 0.8341817584818465, 'colsample_bytree': 0.20200236643352473}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:23:23,316] Trial 432 finished with value: 0.976 and parameters: {'learning_rate': 0.003673296037744527, 'n_estimators': 2384, 'max_depth': 48, 'subsample': 0.8698727682464533, 'colsample_bytree': 0.3366628311552402}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:23:37,329] Trial 433 finished with value: 0.982 and parameters: {'learning_rate': 0.0438017264882017, 'n_estimators': 2552, 'max_depth': 9, 'subsample': 0.7453375297187859, 'colsample_bytree': 0.1829271609226876}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:23:51,425] Trial 434 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.06601863783132383, 'n_estimators': 2868, 'max_depth': 8, 'subsample': 0.9029152676608164, 'colsample_bytree': 0.15508972750636194}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:24:00,731] Trial 435 finished with value: 0.9719999999999999 and parameters: {'learning_rate': 0.029617846955834977, 'n_estimators': 2479, 'max_depth': 50, 'subsample': 0.29995791222117335, 'colsample_bytree': 0.10021365016573064}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:24:14,406] Trial 436 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.049782731455394254, 'n_estimators': 2783, 'max_depth': 18, 'subsample': 0.8003465368098449, 'colsample_bytree': 0.12461051481526422}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:25:16,739] Trial 437 finished with value: 0.968 and parameters: {'learning_rate': 0.0006112253883261652, 'n_estimators': 2694, 'max_depth': 10, 'subsample': 0.8499731017911231, 'colsample_bytree': 0.3091378812408677}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:25:30,449] Trial 438 finished with value: 0.982 and parameters: {'learning_rate': 0.037768496571001016, 'n_estimators': 2440, 'max_depth': 19, 'subsample': 0.8863947352039157, 'colsample_bytree': 0.16729197315673483}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:25:43,963] Trial 439 finished with value: 0.984 and parameters: {'learning_rate': 0.05952220440345988, 'n_estimators': 2920, 'max_depth': 12, 'subsample': 0.7825963032974728, 'colsample_bytree': 0.14220865567044513}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:25:55,726] Trial 440 finished with value: 0.978 and parameters: {'learning_rate': 0.0790772307866498, 'n_estimators': 2928, 'max_depth': 12, 'subsample': 0.7835386918005327, 'colsample_bytree': 0.13401235556980995}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:26:10,460] Trial 441 finished with value: 0.982 and parameters: {'learning_rate': 0.05969416867421013, 'n_estimators': 2947, 'max_depth': 11, 'subsample': 0.676914720420764, 'colsample_bytree': 0.1489117149594567}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:26:24,949] Trial 442 finished with value: 0.982 and parameters: {'learning_rate': 0.024605924060583435, 'n_estimators': 2606, 'max_depth': 12, 'subsample': 0.808998267382938, 'colsample_bytree': 0.12505098864612982}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:26:38,177] Trial 443 finished with value: 0.982 and parameters: {'learning_rate': 0.06992268434096503, 'n_estimators': 2555, 'max_depth': 10, 'subsample': 0.8309532459971967, 'colsample_bytree': 0.1534901148741292}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:26:50,250] Trial 444 finished with value: 0.9719999999999999 and parameters: {'learning_rate': 0.045032767360505876, 'n_estimators': 2399, 'max_depth': 26, 'subsample': 0.18466891546636, 'colsample_bytree': 0.3565299861220639}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:27:48,630] Trial 445 finished with value: 0.962 and parameters: {'learning_rate': 7.760596707689938e-05, 'n_estimators': 2498, 'max_depth': 13, 'subsample': 0.6094741780964302, 'colsample_bytree': 0.4679033753702734}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:28:02,981] Trial 446 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.05890945850112295, 'n_estimators': 2998, 'max_depth': 16, 'subsample': 0.7783328944863969, 'colsample_bytree': 0.11608107302064094}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:30:38,681] Trial 447 finished with value: 0.962 and parameters: {'learning_rate': 5.401258262956541e-05, 'n_estimators': 2859, 'max_depth': 32, 'subsample': 0.8212578073707967, 'colsample_bytree': 0.9381129836166531}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:31:09,666] Trial 448 finished with value: 0.9719999999999999 and parameters: {'learning_rate': 0.0011133827105906792, 'n_estimators': 2334, 'max_depth': 31, 'subsample': 0.8688821507008425, 'colsample_bytree': 0.14307778409561375}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:31:23,489] Trial 449 finished with value: 0.978 and parameters: {'learning_rate': 0.08290569736166016, 'n_estimators': 2646, 'max_depth': 14, 'subsample': 0.6514440662524584, 'colsample_bytree': 0.17427134808811132}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:31:49,142] Trial 450 finished with value: 0.9739999999999999 and parameters: {'learning_rate': 0.0015642689503743, 'n_estimators': 2449, 'max_depth': 35, 'subsample': 0.5671612578499619, 'colsample_bytree': 0.16094334621489065}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:32:16,439] Trial 451 finished with value: 0.976 and parameters: {'learning_rate': 0.03515710604878672, 'n_estimators': 2908, 'max_depth': 37, 'subsample': 0.7993913429476679, 'colsample_bytree': 0.8863096114861579}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:32:29,437] Trial 452 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.05091227977742159, 'n_estimators': 2541, 'max_depth': 28, 'subsample': 0.47472940332157043, 'colsample_bytree': 0.11946195517826641}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:33:01,789] Trial 453 finished with value: 0.966 and parameters: {'learning_rate': 0.0005334734096578166, 'n_estimators': 2794, 'max_depth': 21, 'subsample': 0.7047244506908688, 'colsample_bytree': 0.13628810790054247}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:33:16,156] Trial 454 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.06878083086722425, 'n_estimators': 2737, 'max_depth': 9, 'subsample': 0.6364780278290202, 'colsample_bytree': 0.1870597777605668}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:33:35,550] Trial 455 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.01106835431448379, 'n_estimators': 2935, 'max_depth': 12, 'subsample': 0.8509942321054343, 'colsample_bytree': 0.16622147291723013}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:34:21,531] Trial 456 finished with value: 0.9739999999999999 and parameters: {'learning_rate': 0.001850583314603266, 'n_estimators': 2497, 'max_depth': 30, 'subsample': 0.8890761765536336, 'colsample_bytree': 0.2689506250265279}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:34:43,138] Trial 457 finished with value: 0.9739999999999999 and parameters: {'learning_rate': 0.005282842758695457, 'n_estimators': 2005, 'max_depth': 39, 'subsample': 0.5890635042562563, 'colsample_bytree': 0.28779109475253073}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:34:58,538] Trial 458 finished with value: 0.978 and parameters: {'learning_rate': 0.027305978023846586, 'n_estimators': 2835, 'max_depth': 14, 'subsample': 0.8339437641993213, 'colsample_bytree': 0.14377148554407923}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:35:08,986] Trial 459 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.09911658283958667, 'n_estimators': 1754, 'max_depth': 41, 'subsample': 0.9275475143477443, 'colsample_bytree': 0.1992614868739115}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:36:01,447] Trial 460 finished with value: 0.976 and parameters: {'learning_rate': 0.002375034051916533, 'n_estimators': 2397, 'max_depth': 8, 'subsample': 0.813824782164644, 'colsample_bytree': 0.4201422297860415}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:36:14,570] Trial 461 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.04059407938871208, 'n_estimators': 2615, 'max_depth': 46, 'subsample': 0.5302654499324322, 'colsample_bytree': 0.11861065084976541}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:37:09,412] Trial 462 finished with value: 0.976 and parameters: {'learning_rate': 0.003408934076022315, 'n_estimators': 2279, 'max_depth': 17, 'subsample': 0.7707086045285004, 'colsample_bytree': 0.5922185525816891}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:37:21,982] Trial 463 finished with value: 0.968 and parameters: {'learning_rate': 0.055228488926491376, 'n_estimators': 2688, 'max_depth': 25, 'subsample': 0.10716856032178768, 'colsample_bytree': 0.18053071623590924}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:37:35,085] Trial 464 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.022122599913755352, 'n_estimators': 2451, 'max_depth': 13, 'subsample': 0.6815385544482074, 'colsample_bytree': 0.148641855043728}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:38:02,528] Trial 465 finished with value: 0.976 and parameters: {'learning_rate': 0.031076136414383303, 'n_estimators': 2953, 'max_depth': 48, 'subsample': 0.9088946313743338, 'colsample_bytree': 0.8050930361971737}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:38:17,833] Trial 466 finished with value: 0.976 and parameters: {'learning_rate': 0.0809840599893975, 'n_estimators': 2553, 'max_depth': 7, 'subsample': 0.8604359817251472, 'colsample_bytree': 0.3765184229554884}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:38:37,747] Trial 467 finished with value: 0.982 and parameters: {'learning_rate': 0.045910048915949006, 'n_estimators': 2893, 'max_depth': 10, 'subsample': 0.7302058038695303, 'colsample_bytree': 0.495110051334012}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:38:43,637] Trial 468 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.06352814159451237, 'n_estimators': 545, 'max_depth': 22, 'subsample': 0.794326271030298, 'colsample_bytree': 0.2228455556989514}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:38:53,406] Trial 469 finished with value: 0.978 and parameters: {'learning_rate': 0.036765987814249744, 'n_estimators': 2364, 'max_depth': 9, 'subsample': 0.8449487952676524, 'colsample_bytree': 0.11303718990719056}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:39:06,374] Trial 470 finished with value: 0.978 and parameters: {'learning_rate': 0.05347527917794217, 'n_estimators': 2502, 'max_depth': 43, 'subsample': 0.9648474846701683, 'colsample_bytree': 0.16519254026469973}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:39:39,080] Trial 471 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.009609604641198146, 'n_estimators': 2595, 'max_depth': 15, 'subsample': 0.8739810783191756, 'colsample_bytree': 0.4537308783272238}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:40:02,182] Trial 472 finished with value: 0.976 and parameters: {'learning_rate': 0.003062636109520345, 'n_estimators': 2781, 'max_depth': 13, 'subsample': 0.618154018698329, 'colsample_bytree': 0.13390753314020037}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:40:28,591] Trial 473 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.015673433947016067, 'n_estimators': 2868, 'max_depth': 50, 'subsample': 0.7512826564946679, 'colsample_bytree': 0.47740357171577175}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:41:03,361] Trial 474 finished with value: 0.9639999999999999 and parameters: {'learning_rate': 1.1829431119998667e-05, 'n_estimators': 2423, 'max_depth': 27, 'subsample': 0.7165503790426021, 'colsample_bytree': 0.20337539631473067}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:41:27,194] Trial 475 finished with value: 0.978 and parameters: {'learning_rate': 0.07238415362949886, 'n_estimators': 2995, 'max_depth': 8, 'subsample': 0.9451568866850779, 'colsample_bytree': 0.7517151477797778}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:41:37,411] Trial 476 finished with value: 0.976 and parameters: {'learning_rate': 0.04396695569097593, 'n_estimators': 2653, 'max_depth': 36, 'subsample': 0.8358608596547132, 'colsample_bytree': 0.10186548985638594}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:42:20,993] Trial 477 finished with value: 0.962 and parameters: {'learning_rate': 1.4743039024778859e-05, 'n_estimators': 1889, 'max_depth': 11, 'subsample': 0.6993187499520633, 'colsample_bytree': 0.38358069741693224}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:42:54,371] Trial 478 finished with value: 0.966 and parameters: {'learning_rate': 0.00029367102932381515, 'n_estimators': 2529, 'max_depth': 5, 'subsample': 0.891452254570174, 'colsample_bytree': 0.15426661820048565}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:44:17,148] Trial 479 finished with value: 0.954 and parameters: {'learning_rate': 0.00011498162388749412, 'n_estimators': 2730, 'max_depth': 12, 'subsample': 0.5459622314459551, 'colsample_bytree': 0.6959327612582104}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:44:30,033] Trial 480 finished with value: 0.978 and parameters: {'learning_rate': 0.08558381302492457, 'n_estimators': 2323, 'max_depth': 21, 'subsample': 0.8180268773216618, 'colsample_bytree': 0.24482373737721283}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:44:59,253] Trial 481 finished with value: 0.9719999999999999 and parameters: {'learning_rate': 0.001119365875163326, 'n_estimators': 2944, 'max_depth': 16, 'subsample': 0.6674514596534308, 'colsample_bytree': 0.13445963764389973}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:45:36,522] Trial 482 finished with value: 0.966 and parameters: {'learning_rate': 0.0002565622840932622, 'n_estimators': 2467, 'max_depth': 15, 'subsample': 0.7791552586072841, 'colsample_bytree': 0.18643953067398514}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:46:54,375] Trial 483 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 1.0154507188951036e-05, 'n_estimators': 2846, 'max_depth': 40, 'subsample': 0.8006264568934983, 'colsample_bytree': 0.43017798622888936}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:47:32,069] Trial 484 finished with value: 0.976 and parameters: {'learning_rate': 0.006914260670326676, 'n_estimators': 2132, 'max_depth': 24, 'subsample': 0.8599320921989019, 'colsample_bytree': 0.5328696924845765}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:47:56,639] Trial 485 finished with value: 0.982 and parameters: {'learning_rate': 0.01862133410085734, 'n_estimators': 2586, 'max_depth': 45, 'subsample': 0.7401108415198435, 'colsample_bytree': 0.5672676195690247}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:48:11,387] Trial 486 finished with value: 0.978 and parameters: {'learning_rate': 0.061193121240587595, 'n_estimators': 2902, 'max_depth': 19, 'subsample': 0.5743170942163268, 'colsample_bytree': 0.16723745920894476}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:48:36,386] Trial 487 finished with value: 0.976 and parameters: {'learning_rate': 0.0019078906753437952, 'n_estimators': 2399, 'max_depth': 18, 'subsample': 0.881496118729417, 'colsample_bytree': 0.10023465836542025}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:48:48,015] Trial 488 finished with value: 0.982 and parameters: {'learning_rate': 0.028855051486109246, 'n_estimators': 2514, 'max_depth': 9, 'subsample': 0.9105556303304406, 'colsample_bytree': 0.13123048620825756}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:49:24,119] Trial 489 finished with value: 0.97 and parameters: {'learning_rate': 0.0007345719635284752, 'n_estimators': 2799, 'max_depth': 8, 'subsample': 0.7617229968231713, 'colsample_bytree': 0.1514348904797802}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:49:59,134] Trial 490 finished with value: 0.962 and parameters: {'learning_rate': 7.710944036249547e-05, 'n_estimators': 2450, 'max_depth': 6, 'subsample': 0.645603861378161, 'colsample_bytree': 0.2189033316395767}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:50:24,746] Trial 491 finished with value: 0.978 and parameters: {'learning_rate': 0.003975226035210669, 'n_estimators': 2694, 'max_depth': 33, 'subsample': 0.8483037449444439, 'colsample_bytree': 0.1842817717319194}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:50:56,454] Trial 492 finished with value: 0.974 and parameters: {'learning_rate': 0.05012084605266669, 'n_estimators': 2920, 'max_depth': 7, 'subsample': 0.827812834158305, 'colsample_bytree': 0.5931774012170248}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:53:11,930] Trial 493 finished with value: 0.9640000000000001 and parameters: {'learning_rate': 0.00020444668810990074, 'n_estimators': 2553, 'max_depth': 11, 'subsample': 0.8654208957771077, 'colsample_bytree': 0.7751139683574784}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:53:26,660] Trial 494 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.037879227936167284, 'n_estimators': 2960, 'max_depth': 23, 'subsample': 0.6843187213490097, 'colsample_bytree': 0.12156447930155648}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:53:42,950] Trial 495 finished with value: 0.978 and parameters: {'learning_rate': 0.06997235935653995, 'n_estimators': 2632, 'max_depth': 30, 'subsample': 0.7887232683541084, 'colsample_bytree': 0.40424242154802376}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:53:59,430] Trial 496 finished with value: 0.976 and parameters: {'learning_rate': 0.09868726881214762, 'n_estimators': 2239, 'max_depth': 27, 'subsample': 0.814341033504367, 'colsample_bytree': 0.7110774305465833}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:54:14,598] Trial 497 finished with value: 0.982 and parameters: {'learning_rate': 0.061662990351275884, 'n_estimators': 2994, 'max_depth': 17, 'subsample': 0.7184840418622332, 'colsample_bytree': 0.1720467208844949}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:54:30,465] Trial 498 finished with value: 0.9800000000000001 and parameters: {'learning_rate': 0.03198228968550267, 'n_estimators': 2811, 'max_depth': 20, 'subsample': 0.6021109644122946, 'colsample_bytree': 0.1431491516589034}. Best is trial 97 with value: 0.984.\n",
            "[I 2023-09-21 19:54:44,073] Trial 499 finished with value: 0.9799999999999999 and parameters: {'learning_rate': 0.04447327473550147, 'n_estimators': 2378, 'max_depth': 5, 'subsample': 0.8983363654837053, 'colsample_bytree': 0.19764404743867708}. Best is trial 97 with value: 0.984.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "XGB best parameters:  {'learning_rate': 0.03715547309484834, 'n_estimators': 2529, 'max_depth': 7, 'subsample': 0.8646850677612571, 'colsample_bytree': 0.1453916995501207}\n"
          ]
        }
      ],
      "source": [
        "run_optimization('xgb', Sudan_train_data, 500)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QzTW7ldoC1CA"
      },
      "source": [
        "**XGBoost Model Training**"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "In this section, we establish a dedicated model for each country, leveraging the optimized hyperparameters obtained earlier through Optuna. These tuned models are subsequently harnessed to produce predictions for each respective country based on the test dataframes and the selected features (check previous sections)."
      ],
      "metadata": {
        "id": "njP6qEXGs-co"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ifoQJdNpaE7t"
      },
      "outputs": [],
      "source": [
        "afgh_xgb = XGBClassifier(\n",
        "        learning_rate=0.0052493969604778335,\n",
        "        n_estimators=2063,\n",
        "        max_depth=17,\n",
        "        subsample=0.4686499286014045,\n",
        "        colsample_bytree=0.7475032992018813,\n",
        "        n_jobs=-1,\n",
        "        objective='binary:logistic',\n",
        "        eval_metric='logloss',\n",
        "        random_state=SEED\n",
        "    )\n",
        "\n",
        "afgh_train_X = Afghanistan_train_data.drop(['ID', 'Target'], axis = 1).fillna(0)\n",
        "afgn_train_Y = Afghanistan_train_data.Target\n",
        "\n",
        "afgh_xgb.fit(afgh_train_X, afgn_train_Y)\n",
        "\n",
        "# Make predictions\n",
        "Afghanistan_test_data = Afghanistan_test_data [relevant_features['Afghanistan'] + stable_cols_Afgh[:1]]\n",
        "afgh_test_X = Afghanistan_test_data.drop(['ID'], axis = 1).fillna(0)\n",
        "afgh_predictions = afgh_xgb.predict(afgh_test_X)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "qCBjUnTdbhGL"
      },
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      "source": [
        "Iran_xgb = XGBClassifier(\n",
        "        learning_rate=0.04074652544112853,\n",
        "        n_estimators=454,\n",
        "        max_depth=8,\n",
        "        subsample=0.3153099125619524,\n",
        "        colsample_bytree=0.1593272485470127,\n",
        "        n_jobs=-1,\n",
        "        objective='binary:logistic',\n",
        "        eval_metric='logloss',\n",
        "        random_state=SEED\n",
        "    )\n",
        "\n",
        "Iran_train_X = Iran_train_data.drop(['ID', 'Target'], axis = 1).fillna(0)\n",
        "Iran_train_Y = Iran_train_data.Target\n",
        "\n",
        "Iran_xgb.fit(Iran_train_X, Iran_train_Y)\n",
        "\n",
        "# Make predictions\n",
        "Iran_test_X = Iran_test_data [relevant_features['Iran'] + stable_cols_Iran[:2]]\n",
        "Iran_predictions = Iran_xgb.predict(Iran_test_X.drop(['ID'], axis = 1).fillna(0))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7-4zMNt2cdOL"
      },
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      "source": [
        "Sudan_xgb = XGBClassifier(\n",
        "        learning_rate=0.03715547309484834,\n",
        "        n_estimators=2529,\n",
        "        max_depth=7,\n",
        "        subsample=0.8646850677612571,\n",
        "        colsample_bytree=0.1453916995501207,\n",
        "        n_jobs=-1,\n",
        "        objective='binary:logistic',\n",
        "        eval_metric='logloss',\n",
        "        random_state=SEED\n",
        "    )\n",
        "\n",
        "Sudan_train_X = Sudan_train_data.drop(['ID', 'Target'], axis = 1).fillna(0)\n",
        "Sudan_train_Y = Sudan_train_data.Target\n",
        "\n",
        "Sudan_xgb.fit(Sudan_train_X, Sudan_train_Y)\n",
        "\n",
        "# Make predictions\n",
        "Sudan_test_X = Sudan_test_data [relevant_features['Sudan'] + stable_cols_Sudan[:2]]\n",
        "Sudan_predictions = Sudan_xgb.predict(Sudan_test_X.drop(['ID'], axis = 1).fillna(0))"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The three prediction dataframes (for each country) are merged into one submission file."
      ],
      "metadata": {
        "id": "F6ABgRrstu3P"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Create a submission file\n",
        "Afgh_predictions_df = pd.DataFrame({'ID': Afghanistan_test_data.ID, 'Target': afgh_predictions})\n",
        "Sudan_predictions_df = pd.DataFrame({'ID': Sudan_test_data.ID, 'Target': Sudan_predictions})\n",
        "Iran_predictions_df = pd.DataFrame({'ID': Iran_test_data.ID, 'Target': Iran_predictions})\n",
        "\n",
        "submission_file = pd.concat([Afgh_predictions_df,\n",
        "                             Sudan_predictions_df,\n",
        "                             Iran_predictions_df\n",
        "                             ], axis=0)\n",
        "\n",
        "submission_file.to_csv('XGB_submission.csv', index = False)"
      ],
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        "id": "rzr5IkjHKMx2"
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      "execution_count": null,
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