lb-0-15-icr-simple-trial-lgbm-optuna.ipynb

{"cells":[{"source":"<a href=\"https://www.kaggle.com/code/yaaangzhou/icr-eda-modelling?scriptVersionId=138623811\" target=\"_blank\"><img align=\"left\" alt=\"Kaggle\" title=\"Open in Kaggle\" src=\"https://kaggle.com/static/images/open-in-kaggle.svg\"></a>","metadata":{},"cell_type":"markdown"},{"cell_type":"code","execution_count":1,"id":"6032cb7d","metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","execution":{"iopub.execute_input":"2023-08-01T22:01:58.810205Z","iopub.status.busy":"2023-08-01T22:01:58.809701Z","iopub.status.idle":"2023-08-01T22:01:58.824656Z","shell.execute_reply":"2023-08-01T22:01:58.823657Z"},"papermill":{"duration":0.024768,"end_time":"2023-08-01T22:01:58.827065","exception":false,"start_time":"2023-08-01T22:01:58.802297","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["/kaggle/input/icr-identify-age-related-conditions/sample_submission.csv\n","/kaggle/input/icr-identify-age-related-conditions/greeks.csv\n","/kaggle/input/icr-identify-age-related-conditions/train.csv\n","/kaggle/input/icr-identify-age-related-conditions/test.csv\n"]}],"source":["# This Python 3 environment comes with many helpful analytics libraries installed\n","# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n","# For example, here's several helpful packages to load\n","\n","import numpy as np # linear algebra\n","import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n","\n","# Input data files are available in the read-only \"../input/\" directory\n","# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n","\n","import os\n","for dirname, _, filenames in os.walk('/kaggle/input'):\n","    for filename in filenames:\n","        print(os.path.join(dirname, filename))\n","\n","# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n","# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"]},{"cell_type":"markdown","id":"c3236b3f","metadata":{"papermill":{"duration":0.004729,"end_time":"2023-08-01T22:01:58.83691","exception":false,"start_time":"2023-08-01T22:01:58.832181","status":"completed"},"tags":[]},"source":["# Imports"]},{"cell_type":"code","execution_count":2,"id":"cd28df48","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:01:58.849349Z","iopub.status.busy":"2023-08-01T22:01:58.848608Z","iopub.status.idle":"2023-08-01T22:02:01.045977Z","shell.execute_reply":"2023-08-01T22:02:01.045157Z"},"papermill":{"duration":2.206048,"end_time":"2023-08-01T22:02:01.048399","exception":false,"start_time":"2023-08-01T22:01:58.842351","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.10/site-packages/scipy/__init__.py:146: UserWarning: A NumPy version >=1.16.5 and <1.23.0 is required for this version of SciPy (detected version 1.23.5\n","  warnings.warn(f\"A NumPy version >={np_minversion} and <{np_maxversion}\"\n"]}],"source":["import numpy as np\n","import pandas as pd\n","from sklearn.metrics import log_loss\n","from catboost import Pool, CatBoostClassifier\n","from sklearn.ensemble import RandomForestClassifier\n","from sklearn.linear_model import LogisticRegression\n","from sklearn.model_selection import StratifiedKFold\n","from sklearn.impute import SimpleImputer\n","import matplotlib.pyplot as plt\n","import seaborn as sns"]},{"cell_type":"code","execution_count":3,"id":"c77408b6","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:02:01.06074Z","iopub.status.busy":"2023-08-01T22:02:01.060095Z","iopub.status.idle":"2023-08-01T22:02:01.113845Z","shell.execute_reply":"2023-08-01T22:02:01.112787Z"},"papermill":{"duration":0.062691,"end_time":"2023-08-01T22:02:01.116288","exception":false,"start_time":"2023-08-01T22:02:01.053597","status":"completed"},"tags":[]},"outputs":[],"source":["# Load the data\n","train = pd.read_csv('/kaggle/input/icr-identify-age-related-conditions/train.csv')\n","test = pd.read_csv('/kaggle/input/icr-identify-age-related-conditions/test.csv')\n","greeks = pd.read_csv('/kaggle/input/icr-identify-age-related-conditions/greeks.csv')\n","sample_submission = pd.read_csv('/kaggle/input/icr-identify-age-related-conditions/sample_submission.csv')\n"]},{"cell_type":"code","execution_count":4,"id":"eaef61ee","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:02:01.128697Z","iopub.status.busy":"2023-08-01T22:02:01.127836Z","iopub.status.idle":"2023-08-01T22:02:01.133783Z","shell.execute_reply":"2023-08-01T22:02:01.133078Z"},"papermill":{"duration":0.013965,"end_time":"2023-08-01T22:02:01.135586","exception":false,"start_time":"2023-08-01T22:02:01.121621","status":"completed"},"tags":[]},"outputs":[],"source":["numerical_features = ['AB', 'AF', 'AH', 'AM', 'AR', 'AX', 'AY', 'AZ',\n","                      'BC', 'BD', 'BN', 'BP', 'BQ', 'BR', 'BZ',\n","                      'CB', 'CC', 'CD', 'CF', 'CH', 'CL', 'CR', 'CS', 'CU', 'CW',\n","                      'DA', 'DE', 'DF', 'DH', 'DI', 'DL', 'DN', 'DU', 'DV', 'DY',\n","                      'EB', 'EE', 'EG', 'EH', 'EL', 'EP', 'EU',\n","                      'FC', 'FD', 'FE', 'FI', 'FL', 'FR', 'FS',\n","                      'GB', 'GE', 'GF', 'GH', 'GI', 'GL']\n","categorical_features = ['EJ']\n","features = numerical_features + categorical_features"]},{"cell_type":"code","execution_count":5,"id":"1b58b68b","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:02:01.147382Z","iopub.status.busy":"2023-08-01T22:02:01.146758Z","iopub.status.idle":"2023-08-01T22:02:01.157176Z","shell.execute_reply":"2023-08-01T22:02:01.156171Z"},"papermill":{"duration":0.018905,"end_time":"2023-08-01T22:02:01.159558","exception":false,"start_time":"2023-08-01T22:02:01.140653","status":"completed"},"tags":[]},"outputs":[],"source":["train['EJ'] = train['EJ'].replace({'A': 0, 'B': 1})\n","test['EJ'] = test['EJ'].replace({'A': 0, 'B': 1})"]},{"cell_type":"code","execution_count":6,"id":"3f108bd7","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:02:01.17134Z","iopub.status.busy":"2023-08-01T22:02:01.170961Z","iopub.status.idle":"2023-08-01T22:02:01.182845Z","shell.execute_reply":"2023-08-01T22:02:01.182131Z"},"papermill":{"duration":0.020051,"end_time":"2023-08-01T22:02:01.1848","exception":false,"start_time":"2023-08-01T22:02:01.164749","status":"completed"},"tags":[]},"outputs":[],"source":["X=train.drop(\"Class\",axis=1)\n","y=train[\"Class\"]\n","\n","X_test=test.copy()"]},{"cell_type":"code","execution_count":7,"id":"0f3c6542","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:02:01.196833Z","iopub.status.busy":"2023-08-01T22:02:01.196143Z","iopub.status.idle":"2023-08-01T22:02:01.20339Z","shell.execute_reply":"2023-08-01T22:02:01.202624Z"},"papermill":{"duration":0.015354,"end_time":"2023-08-01T22:02:01.205474","exception":false,"start_time":"2023-08-01T22:02:01.19012","status":"completed"},"tags":[]},"outputs":[],"source":["X = X.drop('Id',axis = 1)"]},{"cell_type":"code","execution_count":8,"id":"b725fe11","metadata":{"_kg_hide-output":true,"execution":{"iopub.execute_input":"2023-08-01T22:02:01.217928Z","iopub.status.busy":"2023-08-01T22:02:01.217193Z","iopub.status.idle":"2023-08-01T22:03:33.342591Z","shell.execute_reply":"2023-08-01T22:03:33.341615Z"},"papermill":{"duration":92.133978,"end_time":"2023-08-01T22:03:33.344531","exception":false,"start_time":"2023-08-01T22:02:01.210553","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["\u001b[32m[I 2023-08-01 22:02:01,774]\u001b[0m A new study created in memory with name: no-name-4f0858e0-601c-45ec-9ab7-ddbdeed40c04\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:02,309]\u001b[0m Trial 0 finished with value: 0.9539388721480844 and parameters: {'n_estimators': 400, 'max_depth': 3, 'learning_rate': 0.008553819527866234, 'subsample': 0.6599650667319352, 'colsample_bytree': 0.6607542562151905, 'gamma': 0.15083253023400145}. Best is trial 0 with value: 0.9539388721480844.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:03,404]\u001b[0m Trial 1 finished with value: 0.991820921222557 and parameters: {'n_estimators': 700, 'max_depth': 5, 'learning_rate': 0.023196208779715143, 'subsample': 0.5961699270654532, 'colsample_bytree': 0.9636566419734005, 'gamma': 0.06706740892391581}. Best is trial 1 with value: 0.991820921222557.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:03,695]\u001b[0m Trial 2 finished with value: 0.9332759362892811 and parameters: {'n_estimators': 200, 'max_depth': 3, 'learning_rate': 0.0013064314558678374, 'subsample': 0.8986769435181889, 'colsample_bytree': 0.6688817089965171, 'gamma': 0.8812201379621665}. Best is trial 1 with value: 0.991820921222557.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:04,512]\u001b[0m Trial 3 finished with value: 0.988807576409815 and parameters: {'n_estimators': 500, 'max_depth': 6, 'learning_rate': 0.040379900873356946, 'subsample': 0.6373121024518067, 'colsample_bytree': 0.9962279328271755, 'gamma': 0.07526740489881134}. Best is trial 1 with value: 0.991820921222557.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:05,330]\u001b[0m Trial 4 finished with value: 0.9832113646147222 and parameters: {'n_estimators': 400, 'max_depth': 6, 'learning_rate': 0.02530141829126482, 'subsample': 0.8511543930534021, 'colsample_bytree': 0.6687167521172734, 'gamma': 0.44118108956419905}. Best is trial 1 with value: 0.991820921222557.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:06,276]\u001b[0m Trial 5 finished with value: 0.9517864829961257 and parameters: {'n_estimators': 400, 'max_depth': 7, 'learning_rate': 0.0010804956372250862, 'subsample': 0.7664353834055999, 'colsample_bytree': 0.6984938120769446, 'gamma': 0.013436420609065186}. Best is trial 1 with value: 0.991820921222557.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:07,147]\u001b[0m Trial 6 finished with value: 0.9608265174343521 and parameters: {'n_estimators': 400, 'max_depth': 8, 'learning_rate': 0.006307124672696755, 'subsample': 0.8196699978029813, 'colsample_bytree': 0.5590137832904591, 'gamma': 0.44007003758494767}. Best is trial 1 with value: 0.991820921222557.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:08,259]\u001b[0m Trial 7 finished with value: 0.9896685320705985 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.03945376798270799, 'subsample': 0.7242024407279796, 'colsample_bytree': 0.7395539249310272, 'gamma': 0.0013075637528407154}. Best is trial 1 with value: 0.991820921222557.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:08,693]\u001b[0m Trial 8 finished with value: 0.9332759362892811 and parameters: {'n_estimators': 300, 'max_depth': 3, 'learning_rate': 0.002950306412974825, 'subsample': 0.5734911654817723, 'colsample_bytree': 0.9064738868482773, 'gamma': 0.21600686467723482}. Best is trial 1 with value: 0.991820921222557.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:10,172]\u001b[0m Trial 9 finished with value: 0.9801980198019802 and parameters: {'n_estimators': 900, 'max_depth': 4, 'learning_rate': 0.0055140643894546985, 'subsample': 0.8483060609410111, 'colsample_bytree': 0.685824898008939, 'gamma': 0.750643524108304}. Best is trial 1 with value: 0.991820921222557.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:11,169]\u001b[0m Trial 10 finished with value: 0.9892380542402066 and parameters: {'n_estimators': 700, 'max_depth': 5, 'learning_rate': 0.02181237907899447, 'subsample': 0.5253257588858512, 'colsample_bytree': 0.8381508264055894, 'gamma': 0.027321902358112795}. Best is trial 1 with value: 0.991820921222557.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:12,168]\u001b[0m Trial 11 finished with value: 0.9896685320705985 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.08952783614390752, 'subsample': 0.985911291011654, 'colsample_bytree': 0.8026510332471039, 'gamma': 0.001459694485501214}. Best is trial 1 with value: 0.991820921222557.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:14,512]\u001b[0m Trial 12 finished with value: 0.9888075764098149 and parameters: {'n_estimators': 700, 'max_depth': 10, 'learning_rate': 0.017732911823077967, 'subsample': 0.6941671565235572, 'colsample_bytree': 0.7809366991928539, 'gamma': 0.0010061854706731868}. Best is trial 1 with value: 0.991820921222557.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:15,537]\u001b[0m Trial 13 finished with value: 0.9913904433921653 and parameters: {'n_estimators': 800, 'max_depth': 8, 'learning_rate': 0.06416679823888888, 'subsample': 0.7220901205680392, 'colsample_bytree': 0.88384236778222, 'gamma': 0.007979702939478448}. Best is trial 1 with value: 0.991820921222557.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:16,302]\u001b[0m Trial 14 finished with value: 0.993542832544124 and parameters: {'n_estimators': 700, 'max_depth': 8, 'learning_rate': 0.09538258685614359, 'subsample': 0.6141285991186449, 'colsample_bytree': 0.9800910792412562, 'gamma': 0.009277091549563016}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:16,986]\u001b[0m Trial 15 finished with value: 0.9926818768833405 and parameters: {'n_estimators': 600, 'max_depth': 8, 'learning_rate': 0.09991115036905558, 'subsample': 0.5767753238828575, 'colsample_bytree': 0.9828880764310678, 'gamma': 0.05225825045845726}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:17,651]\u001b[0m Trial 16 finished with value: 0.9883770985794231 and parameters: {'n_estimators': 600, 'max_depth': 8, 'learning_rate': 0.09027826024605028, 'subsample': 0.5040719566360587, 'colsample_bytree': 0.935635829640711, 'gamma': 0.006392803904144521}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:18,460]\u001b[0m Trial 17 finished with value: 0.9832113646147224 and parameters: {'n_estimators': 600, 'max_depth': 9, 'learning_rate': 0.05651712041224566, 'subsample': 0.5904180531934692, 'colsample_bytree': 0.9936329863451926, 'gamma': 0.0295095506654708}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:18,701]\u001b[0m Trial 18 finished with value: 0.9832113646147224 and parameters: {'n_estimators': 100, 'max_depth': 7, 'learning_rate': 0.08861542407717853, 'subsample': 0.6481511958285952, 'colsample_bytree': 0.8840582260472314, 'gamma': 0.004889872097913849}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:19,786]\u001b[0m Trial 19 finished with value: 0.9900990099009901 and parameters: {'n_estimators': 900, 'max_depth': 9, 'learning_rate': 0.04417530457179571, 'subsample': 0.5520330546863519, 'colsample_bytree': 0.939006727393292, 'gamma': 0.01362795425012051}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:21,195]\u001b[0m Trial 20 finished with value: 0.9905294877313818 and parameters: {'n_estimators': 800, 'max_depth': 9, 'learning_rate': 0.014196266964773977, 'subsample': 0.618250509460454, 'colsample_bytree': 0.851382237481234, 'gamma': 0.05195240420630955}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:22,231]\u001b[0m Trial 21 finished with value: 0.9913904433921653 and parameters: {'n_estimators': 700, 'max_depth': 5, 'learning_rate': 0.02949867898480286, 'subsample': 0.5824953537480696, 'colsample_bytree': 0.9522284853360786, 'gamma': 0.06988107849705702}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:22,996]\u001b[0m Trial 22 finished with value: 0.991820921222557 and parameters: {'n_estimators': 600, 'max_depth': 5, 'learning_rate': 0.06113563647011376, 'subsample': 0.5390462620123601, 'colsample_bytree': 0.9915285734123116, 'gamma': 0.12020436592026024}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:24,170]\u001b[0m Trial 23 finished with value: 0.9913904433921653 and parameters: {'n_estimators': 800, 'max_depth': 7, 'learning_rate': 0.030612268307909873, 'subsample': 0.6050430576190532, 'colsample_bytree': 0.9562120595062406, 'gamma': 0.0455187541454873}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:24,933]\u001b[0m Trial 24 finished with value: 0.9892380542402066 and parameters: {'n_estimators': 500, 'max_depth': 6, 'learning_rate': 0.05363948210725327, 'subsample': 0.5540782231328895, 'colsample_bytree': 0.9165926059838859, 'gamma': 0.029146070461395508}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:25,747]\u001b[0m Trial 25 finished with value: 0.9935428325441239 and parameters: {'n_estimators': 700, 'max_depth': 8, 'learning_rate': 0.09399424321643275, 'subsample': 0.6759843123056481, 'colsample_bytree': 0.9709716167263756, 'gamma': 0.018143659953954203}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:26,364]\u001b[0m Trial 26 finished with value: 0.9905294877313818 and parameters: {'n_estimators': 500, 'max_depth': 8, 'learning_rate': 0.09029095232892742, 'subsample': 0.6793365231638725, 'colsample_bytree': 0.9003512620058559, 'gamma': 0.01998001320545089}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:27,360]\u001b[0m Trial 27 finished with value: 0.9926818768833405 and parameters: {'n_estimators': 900, 'max_depth': 9, 'learning_rate': 0.07010611954978886, 'subsample': 0.6392295544709913, 'colsample_bytree': 0.9683754822648536, 'gamma': 0.0037906546714982984}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:28,052]\u001b[0m Trial 28 finished with value: 0.9875161429186397 and parameters: {'n_estimators': 600, 'max_depth': 8, 'learning_rate': 0.09916937979861357, 'subsample': 0.6817327953994223, 'colsample_bytree': 0.9291104103338934, 'gamma': 0.01105188292395449}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:29,050]\u001b[0m Trial 29 finished with value: 0.9913904433921652 and parameters: {'n_estimators': 800, 'max_depth': 7, 'learning_rate': 0.04256772437109662, 'subsample': 0.6270976113300947, 'colsample_bytree': 0.8487227685962901, 'gamma': 0.02425688098032419}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:29,903]\u001b[0m Trial 30 finished with value: 0.9905294877313819 and parameters: {'n_estimators': 700, 'max_depth': 9, 'learning_rate': 0.06885543663622386, 'subsample': 0.6614059298098872, 'colsample_bytree': 0.9902155380752087, 'gamma': 0.016493081293793926}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:30,918]\u001b[0m Trial 31 finished with value: 0.991820921222557 and parameters: {'n_estimators': 900, 'max_depth': 9, 'learning_rate': 0.06580950699120419, 'subsample': 0.6453056135173363, 'colsample_bytree': 0.9624390825636487, 'gamma': 0.0034927801212739514}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:31,912]\u001b[0m Trial 32 finished with value: 0.9926818768833405 and parameters: {'n_estimators': 900, 'max_depth': 8, 'learning_rate': 0.06891953949370369, 'subsample': 0.6140073208888991, 'colsample_bytree': 0.9674280627037031, 'gamma': 0.003306149177633837}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:32,812]\u001b[0m Trial 33 finished with value: 0.9922513990529488 and parameters: {'n_estimators': 700, 'max_depth': 9, 'learning_rate': 0.04939434493809042, 'subsample': 0.5729551564768965, 'colsample_bytree': 0.923164082407349, 'gamma': 0.009391467655341627}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:33,725]\u001b[0m Trial 34 finished with value: 0.9909599655617736 and parameters: {'n_estimators': 800, 'max_depth': 7, 'learning_rate': 0.07507031807996657, 'subsample': 0.6109405364195435, 'colsample_bytree': 0.970133581136615, 'gamma': 0.019367985214654874}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:34,359]\u001b[0m Trial 35 finished with value: 0.9883770985794231 and parameters: {'n_estimators': 500, 'max_depth': 8, 'learning_rate': 0.09725484328253964, 'subsample': 0.6570929909412694, 'colsample_bytree': 0.9932558854480514, 'gamma': 0.006325312011315986}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:35,687]\u001b[0m Trial 36 finished with value: 0.9922513990529488 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.03729635407487058, 'subsample': 0.5808431185394761, 'colsample_bytree': 0.9445176343524665, 'gamma': 0.03729648056697727}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:36,502]\u001b[0m Trial 37 finished with value: 0.9931123547137323 and parameters: {'n_estimators': 600, 'max_depth': 9, 'learning_rate': 0.05167473247648132, 'subsample': 0.635551642169065, 'colsample_bytree': 0.877957685062033, 'gamma': 0.01123291481758662}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:37,042]\u001b[0m Trial 38 finished with value: 0.9857942315970728 and parameters: {'n_estimators': 300, 'max_depth': 6, 'learning_rate': 0.05067916934067468, 'subsample': 0.6986125238856729, 'colsample_bytree': 0.8802761839883639, 'gamma': 0.013951555207126936}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:37,996]\u001b[0m Trial 39 finished with value: 0.987085665088248 and parameters: {'n_estimators': 600, 'max_depth': 7, 'learning_rate': 0.03743947250403778, 'subsample': 0.7549186315023502, 'colsample_bytree': 0.9189907007185808, 'gamma': 0.010493822709447953}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:38,551]\u001b[0m Trial 40 finished with value: 0.9900990099009901 and parameters: {'n_estimators': 400, 'max_depth': 8, 'learning_rate': 0.07659876513240615, 'subsample': 0.5972945432204614, 'colsample_bytree': 0.9060657197574249, 'gamma': 0.019985488639183018}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:39,461]\u001b[0m Trial 41 finished with value: 0.9900990099009901 and parameters: {'n_estimators': 700, 'max_depth': 9, 'learning_rate': 0.05459148691036799, 'subsample': 0.6267944606640053, 'colsample_bytree': 0.9699347937755676, 'gamma': 0.03933206499386383}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:40,164]\u001b[0m Trial 42 finished with value: 0.9922513990529488 and parameters: {'n_estimators': 600, 'max_depth': 10, 'learning_rate': 0.09995052746694881, 'subsample': 0.6381713660236642, 'colsample_bytree': 0.9975851144270992, 'gamma': 0.014001508840388555}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:40,833]\u001b[0m Trial 43 finished with value: 0.9900990099009901 and parameters: {'n_estimators': 500, 'max_depth': 9, 'learning_rate': 0.07571742225684429, 'subsample': 0.6593639715991889, 'colsample_bytree': 0.9476705366282684, 'gamma': 0.008459339839457156}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:41,676]\u001b[0m Trial 44 finished with value: 0.9905294877313818 and parameters: {'n_estimators': 700, 'max_depth': 8, 'learning_rate': 0.079454878674041, 'subsample': 0.7255582147030863, 'colsample_bytree': 0.9642384511132169, 'gamma': 0.024309283314627506}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:42,617]\u001b[0m Trial 45 finished with value: 0.9896685320705984 and parameters: {'n_estimators': 800, 'max_depth': 10, 'learning_rate': 0.05695161772667653, 'subsample': 0.5648576858672983, 'colsample_bytree': 0.9765843906735134, 'gamma': 0.05071654614573422}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:43,277]\u001b[0m Trial 46 finished with value: 0.9931123547137323 and parameters: {'n_estimators': 500, 'max_depth': 9, 'learning_rate': 0.07454625176814673, 'subsample': 0.5948453667157002, 'colsample_bytree': 0.9330621033818007, 'gamma': 0.08933316729414219}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:43,992]\u001b[0m Trial 47 finished with value: 0.9827808867843305 and parameters: {'n_estimators': 400, 'max_depth': 8, 'learning_rate': 0.04355727107676127, 'subsample': 0.5250279813347483, 'colsample_bytree': 0.9292488460731397, 'gamma': 0.14415568204917958}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:45,407]\u001b[0m Trial 48 finished with value: 0.9926818768833405 and parameters: {'n_estimators': 300, 'max_depth': 7, 'learning_rate': 0.08143916022471988, 'subsample': 0.5881776971031464, 'colsample_bytree': 0.8840932857358295, 'gamma': 0.09036089418081744}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:46,255]\u001b[0m Trial 49 finished with value: 0.9909599655617736 and parameters: {'n_estimators': 500, 'max_depth': 10, 'learning_rate': 0.033174933753688865, 'subsample': 0.6042786984158149, 'colsample_bytree': 0.9372948659163104, 'gamma': 0.059207918734281904}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:47,173]\u001b[0m Trial 50 finished with value: 0.988807576409815 and parameters: {'n_estimators': 600, 'max_depth': 9, 'learning_rate': 0.025430769784312707, 'subsample': 0.5601502351698313, 'colsample_bytree': 0.8185200288824817, 'gamma': 0.08637759254237029}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:47,950]\u001b[0m Trial 51 finished with value: 0.991820921222557 and parameters: {'n_estimators': 600, 'max_depth': 9, 'learning_rate': 0.06736450244706524, 'subsample': 0.6327803859311275, 'colsample_bytree': 0.9792262045438291, 'gamma': 0.03347826992966829}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:48,855]\u001b[0m Trial 52 finished with value: 0.9883770985794232 and parameters: {'n_estimators': 700, 'max_depth': 9, 'learning_rate': 0.07832633218236522, 'subsample': 0.6725374823286329, 'colsample_bytree': 0.999431375802297, 'gamma': 0.18069300647529363}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:49,574]\u001b[0m Trial 53 finished with value: 0.991820921222557 and parameters: {'n_estimators': 500, 'max_depth': 8, 'learning_rate': 0.060706174765878834, 'subsample': 0.6410006437099351, 'colsample_bytree': 0.951850888941492, 'gamma': 0.006943823624759247}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:50,252]\u001b[0m Trial 54 finished with value: 0.988807576409815 and parameters: {'n_estimators': 400, 'max_depth': 8, 'learning_rate': 0.04739472963723841, 'subsample': 0.6168327188564805, 'colsample_bytree': 0.9416420348318525, 'gamma': 0.010856392901460338}. Best is trial 14 with value: 0.993542832544124.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:51,192]\u001b[0m Trial 55 finished with value: 0.9944037882049074 and parameters: {'n_estimators': 1000, 'max_depth': 9, 'learning_rate': 0.09866084739963987, 'subsample': 0.5953283278439917, 'colsample_bytree': 0.9010928907261414, 'gamma': 0.0048975409807983355}. Best is trial 55 with value: 0.9944037882049074.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:52,153]\u001b[0m Trial 56 finished with value: 0.9944037882049074 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.09707276860322162, 'subsample': 0.5937611555342861, 'colsample_bytree': 0.8993446941326735, 'gamma': 0.07059359774479801}. Best is trial 55 with value: 0.9944037882049074.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:53,107]\u001b[0m Trial 57 finished with value: 0.9952647438656909 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.08973203280130075, 'subsample': 0.591087415486324, 'colsample_bytree': 0.8678855671947511, 'gamma': 0.06448157899028026}. Best is trial 57 with value: 0.9952647438656909.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:54,037]\u001b[0m Trial 58 finished with value: 0.9948342660352991 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.0870939724965057, 'subsample': 0.5494344048174172, 'colsample_bytree': 0.8719332158821472, 'gamma': 0.005281571667059656}. Best is trial 57 with value: 0.9952647438656909.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:55,065]\u001b[0m Trial 59 finished with value: 0.9909599655617736 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.08176015752885202, 'subsample': 0.5402605970454788, 'colsample_bytree': 0.848755726203092, 'gamma': 0.005142058720098174}. Best is trial 57 with value: 0.9952647438656909.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:56,009]\u001b[0m Trial 60 finished with value: 0.9948342660352991 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.08778735981838187, 'subsample': 0.50650743787445, 'colsample_bytree': 0.8976632275679597, 'gamma': 0.002750929906349811}. Best is trial 57 with value: 0.9952647438656909.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:56,934]\u001b[0m Trial 61 finished with value: 0.9922513990529488 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.08779755845001985, 'subsample': 0.527324087619245, 'colsample_bytree': 0.8639721151828517, 'gamma': 0.0025936032400684897}. Best is trial 57 with value: 0.9952647438656909.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:57,874]\u001b[0m Trial 62 finished with value: 0.9948342660352991 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.09685160832711548, 'subsample': 0.5630988693621025, 'colsample_bytree': 0.90155200042894, 'gamma': 0.0024222787938145487}. Best is trial 57 with value: 0.9952647438656909.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:58,916]\u001b[0m Trial 63 finished with value: 0.9909599655617736 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.06121258727187987, 'subsample': 0.5050441559120595, 'colsample_bytree': 0.8997038614686473, 'gamma': 0.0021079515084600057}. Best is trial 57 with value: 0.9952647438656909.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:02:59,795]\u001b[0m Trial 64 finished with value: 0.993542832544124 and parameters: {'n_estimators': 900, 'max_depth': 10, 'learning_rate': 0.08966304441181344, 'subsample': 0.5491587822525069, 'colsample_bytree': 0.8305804379420115, 'gamma': 0.0018887778920864064}. Best is trial 57 with value: 0.9952647438656909.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:00,690]\u001b[0m Trial 65 finished with value: 0.9969866551872578 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.0996726606561162, 'subsample': 0.5665283767660989, 'colsample_bytree': 0.8699114505283774, 'gamma': 0.004824624322246532}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:01,729]\u001b[0m Trial 66 finished with value: 0.9931123547137323 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.059398221157535236, 'subsample': 0.5647521442454796, 'colsample_bytree': 0.8615768278309409, 'gamma': 0.004615070168899628}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:02,641]\u001b[0m Trial 67 finished with value: 0.9913904433921653 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.09984820954520834, 'subsample': 0.5013704792399091, 'colsample_bytree': 0.8963061560803944, 'gamma': 0.002746959710318989}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:03,541]\u001b[0m Trial 68 finished with value: 0.9926818768833405 and parameters: {'n_estimators': 900, 'max_depth': 10, 'learning_rate': 0.08132683579558024, 'subsample': 0.572304320584717, 'colsample_bytree': 0.8658267904599085, 'gamma': 0.0015343044222379267}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:04,484]\u001b[0m Trial 69 finished with value: 0.993542832544124 and parameters: {'n_estimators': 900, 'max_depth': 10, 'learning_rate': 0.06541603106273679, 'subsample': 0.54418958239499, 'colsample_bytree': 0.9108400359919719, 'gamma': 0.0011350722160519662}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:05,465]\u001b[0m Trial 70 finished with value: 0.9922513990529488 and parameters: {'n_estimators': 1000, 'max_depth': 3, 'learning_rate': 0.08492245664258906, 'subsample': 0.5175744860991892, 'colsample_bytree': 0.8912601196485338, 'gamma': 0.0049391400240863985}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:06,451]\u001b[0m Trial 71 finished with value: 0.9892380542402066 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.07089101925253583, 'subsample': 0.5542430360550047, 'colsample_bytree': 0.8707195528042665, 'gamma': 0.003481388757516889}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:07,416]\u001b[0m Trial 72 finished with value: 0.9922513990529488 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.08712527019782274, 'subsample': 0.5818774821816157, 'colsample_bytree': 0.90860026478179, 'gamma': 0.004078793655341541}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:08,284]\u001b[0m Trial 73 finished with value: 0.9939733103745158 and parameters: {'n_estimators': 900, 'max_depth': 10, 'learning_rate': 0.09468677012640575, 'subsample': 0.6008923859821673, 'colsample_bytree': 0.8356347612813866, 'gamma': 0.002801167133629624}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:09,123]\u001b[0m Trial 74 finished with value: 0.9939733103745156 and parameters: {'n_estimators': 900, 'max_depth': 10, 'learning_rate': 0.09787437030547126, 'subsample': 0.5324447780027346, 'colsample_bytree': 0.8433578364597332, 'gamma': 0.0021992438295899345}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:10,139]\u001b[0m Trial 75 finished with value: 0.991820921222557 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.06344740957737752, 'subsample': 0.5981554376277823, 'colsample_bytree': 0.8293756852199053, 'gamma': 0.0030613464916922385}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:11,065]\u001b[0m Trial 76 finished with value: 0.9948342660352992 and parameters: {'n_estimators': 900, 'max_depth': 4, 'learning_rate': 0.06961607978763347, 'subsample': 0.5139854595372121, 'colsample_bytree': 0.8845625571472305, 'gamma': 0.00258677901038003}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:12,013]\u001b[0m Trial 77 finished with value: 0.991820921222557 and parameters: {'n_estimators': 1000, 'max_depth': 3, 'learning_rate': 0.0709059310575995, 'subsample': 0.5345002054078006, 'colsample_bytree': 0.8763943086217206, 'gamma': 0.0016529321964779394}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:12,985]\u001b[0m Trial 78 finished with value: 0.9935428325441239 and parameters: {'n_estimators': 900, 'max_depth': 5, 'learning_rate': 0.05424843642817331, 'subsample': 0.5133386150375803, 'colsample_bytree': 0.8898829333788025, 'gamma': 0.005579576536031356}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:14,052]\u001b[0m Trial 79 finished with value: 0.993542832544124 and parameters: {'n_estimators': 1000, 'max_depth': 4, 'learning_rate': 0.04790476418256916, 'subsample': 0.5451580776197149, 'colsample_bytree': 0.8577529846227848, 'gamma': 0.0038871260492403478}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:15,091]\u001b[0m Trial 80 finished with value: 0.9948342660352991 and parameters: {'n_estimators': 1000, 'max_depth': 4, 'learning_rate': 0.08395024118167, 'subsample': 0.5174897772198989, 'colsample_bytree': 0.9170251324539269, 'gamma': 0.007534766095041697}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:17,144]\u001b[0m Trial 81 finished with value: 0.9926818768833405 and parameters: {'n_estimators': 1000, 'max_depth': 4, 'learning_rate': 0.08449567210480263, 'subsample': 0.5175556023885629, 'colsample_bytree': 0.9151619875270355, 'gamma': 0.006961388528130452}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:18,125]\u001b[0m Trial 82 finished with value: 0.9926818768833404 and parameters: {'n_estimators': 1000, 'max_depth': 5, 'learning_rate': 0.07404001237464311, 'subsample': 0.5001235029379447, 'colsample_bytree': 0.8935139748727856, 'gamma': 0.0024279006432547496}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:19,040]\u001b[0m Trial 83 finished with value: 0.9900990099009901 and parameters: {'n_estimators': 900, 'max_depth': 10, 'learning_rate': 0.08748531191315086, 'subsample': 0.5613704134501065, 'colsample_bytree': 0.9201915658965514, 'gamma': 0.004429600081983013}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:20,029]\u001b[0m Trial 84 finished with value: 0.9909599655617736 and parameters: {'n_estimators': 1000, 'max_depth': 4, 'learning_rate': 0.0679076924699567, 'subsample': 0.5307005943493761, 'colsample_bytree': 0.8734590375949152, 'gamma': 0.003093808434189591}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:21,036]\u001b[0m Trial 85 finished with value: 0.9913904433921653 and parameters: {'n_estimators': 1000, 'max_depth': 4, 'learning_rate': 0.056542426558244326, 'subsample': 0.5165743067219472, 'colsample_bytree': 0.9010523583587238, 'gamma': 0.004013448648813773}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:21,915]\u001b[0m Trial 86 finished with value: 0.9922513990529488 and parameters: {'n_estimators': 900, 'max_depth': 4, 'learning_rate': 0.07978038280471539, 'subsample': 0.5714491328218269, 'colsample_bytree': 0.8838845540840218, 'gamma': 0.005614526970049446}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:22,804]\u001b[0m Trial 87 finished with value: 0.9948342660352991 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.09999960098440687, 'subsample': 0.5473252787719092, 'colsample_bytree': 0.8592172541058138, 'gamma': 0.0018163807444126375}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:23,702]\u001b[0m Trial 88 finished with value: 0.9905294877313818 and parameters: {'n_estimators': 900, 'max_depth': 9, 'learning_rate': 0.07320754384485392, 'subsample': 0.551794338702792, 'colsample_bytree': 0.8493657379330477, 'gamma': 0.0019431565850239702}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:24,702]\u001b[0m Trial 89 finished with value: 0.9931123547137323 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.06339357338647131, 'subsample': 0.5329440996502078, 'colsample_bytree': 0.8577327593808435, 'gamma': 0.001355912429354546}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:25,008]\u001b[0m Trial 90 finished with value: 0.978906586310805 and parameters: {'n_estimators': 100, 'max_depth': 9, 'learning_rate': 0.09040354495280487, 'subsample': 0.5823588586891735, 'colsample_bytree': 0.9250274253222044, 'gamma': 0.0034054785876659046}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:25,919]\u001b[0m Trial 91 finished with value: 0.9948342660352991 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.09765950691576988, 'subsample': 0.5430984601493866, 'colsample_bytree': 0.9080615193744905, 'gamma': 0.0017159785899921282}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:26,813]\u001b[0m Trial 92 finished with value: 0.9939733103745158 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.09897227304561297, 'subsample': 0.557445089013826, 'colsample_bytree': 0.8714086264000518, 'gamma': 0.0017697149920071255}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:27,715]\u001b[0m Trial 93 finished with value: 0.9922513990529488 and parameters: {'n_estimators': 900, 'max_depth': 10, 'learning_rate': 0.08046879892120326, 'subsample': 0.5422056926384681, 'colsample_bytree': 0.9136596299251596, 'gamma': 0.0021816774586358575}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:28,626]\u001b[0m Trial 94 finished with value: 0.9956952216960826 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.08893372073554535, 'subsample': 0.5128335423072454, 'colsample_bytree': 0.885343491228931, 'gamma': 0.0023568257388599865}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:29,578]\u001b[0m Trial 95 finished with value: 0.9952647438656909 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.07478948369258838, 'subsample': 0.5146471110718384, 'colsample_bytree': 0.884936293519199, 'gamma': 0.0024768833663784363}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:30,484]\u001b[0m Trial 96 finished with value: 0.9935428325441239 and parameters: {'n_estimators': 900, 'max_depth': 10, 'learning_rate': 0.07118146164044986, 'subsample': 0.5103985679895855, 'colsample_bytree': 0.8784318891950355, 'gamma': 0.0025522940713037854}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:31,499]\u001b[0m Trial 97 finished with value: 0.9913904433921653 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.05915146039855642, 'subsample': 0.5215597269283301, 'colsample_bytree': 0.8866533433996637, 'gamma': 0.0014054008874786364}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:32,422]\u001b[0m Trial 98 finished with value: 0.991820921222557 and parameters: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.08565372366226999, 'subsample': 0.5113019465088682, 'colsample_bytree': 0.8559715506549667, 'gamma': 0.0023004411621442987}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n","/tmp/ipykernel_20/2884987818.py:15: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","/tmp/ipykernel_20/2884987818.py:16: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:17: FutureWarning: suggest_uniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","/tmp/ipykernel_20/2884987818.py:18: FutureWarning: suggest_loguniform has been deprecated in v3.0.0. This feature will be removed in v6.0.0. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Use :func:`~optuna.trial.Trial.suggest_float` instead.\n","  'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","\u001b[32m[I 2023-08-01 22:03:33,335]\u001b[0m Trial 99 finished with value: 0.9892380542402066 and parameters: {'n_estimators': 800, 'max_depth': 6, 'learning_rate': 0.049866998644712446, 'subsample': 0.5236592949825234, 'colsample_bytree': 0.8678836491302185, 'gamma': 0.002948997699522612}. Best is trial 65 with value: 0.9969866551872578.\u001b[0m\n"]},{"data":{"text/plain":["<optuna.study.study.Study at 0x7c77e28f8ca0>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["Best trial: {'n_estimators': 1000, 'max_depth': 10, 'learning_rate': 0.0996726606561162, 'subsample': 0.5665283767660989, 'colsample_bytree': 0.8699114505283774, 'gamma': 0.004824624322246532}\n","Best ROC AUC: 0.9969866551872578\n"]}],"source":["from IPython.display import display\n","import optuna\n","from xgboost import XGBClassifier\n","from sklearn.model_selection import KFold\n","from sklearn.model_selection import train_test_split\n","from sklearn.metrics import roc_auc_score\n","import xgboost as xgb\n","\n","def obj_xgb(trial):\n","    X_train, X_valid, y_train, y_valid = train_test_split(X, y, test_size=0.2, random_state=42)\n","\n","    params = {\n","        'n_estimators': trial.suggest_int('n_estimators', 100, 1000, step=100),\n","        'max_depth': trial.suggest_int('max_depth', 3, 10),\n","        'learning_rate': trial.suggest_loguniform('learning_rate', 0.001, 0.1),\n","        'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n","        'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n","        'gamma': trial.suggest_loguniform('gamma', 0.001, 1.0),\n","        'objective': 'binary:logistic', \n","        'eval_metric': 'logloss', \n","    }\n","\n","    # 构建XGBoost模型\n","    model = xgb.XGBClassifier(**params)\n","    \n","    # 训练模型\n","    model.fit(X_train, y_train)\n","    \n","    # 在验证集上进行预测\n","    y_pred = model.predict_proba(X_valid)[:, 1]  # 预测概率\n","    \n","    # 计算ROC AUC作为目标函数的评估指标\n","    roc_auc = roc_auc_score(y_valid, y_pred)\n","    \n","    return roc_auc\n","\n","# 创建Study对象并进行优化\n","study = optuna.create_study(direction='maximize')\n","study.optimize(obj_xgb, n_trials=100)\n","\n","# 显示Study结果\n","display(study)\n","\n","print('Best trial:', study.best_trial.params)\n","print('Best ROC AUC:', study.best_trial.value)\n"]},{"cell_type":"markdown","id":"f278be84","metadata":{"papermill":{"duration":0.01875,"end_time":"2023-08-01T22:03:33.38233","exception":false,"start_time":"2023-08-01T22:03:33.36358","status":"completed"},"tags":[]},"source":["# Train best model"]},{"cell_type":"code","execution_count":9,"id":"97a259a8","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:03:33.422759Z","iopub.status.busy":"2023-08-01T22:03:33.42238Z","iopub.status.idle":"2023-08-01T22:03:33.651544Z","shell.execute_reply":"2023-08-01T22:03:33.65045Z"},"papermill":{"duration":0.252102,"end_time":"2023-08-01T22:03:33.653909","exception":false,"start_time":"2023-08-01T22:03:33.401807","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["[22:03:33] WARNING: ../src/learner.cc:767: \n","Parameters: { \"n_estimadors\" } are not used.\n","\n"]},{"data":{"text/html":["<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>XGBClassifier(base_score=None, booster=None, callbacks=None,\n","              colsample_bylevel=None, colsample_bynode=None,\n","              colsample_bytree=0.5506296722490095, early_stopping_rounds=None,\n","              enable_categorical=False, eval_metric=None, feature_types=None,\n","              gamma=0.7566166783103027, gpu_id=None, grow_policy=None,\n","              importance_type=None, interaction_constraints=None,\n","              learning_rate=0.0015383461504392903, max_bin=None,\n","              max_cat_threshold=None, max_cat_to_onehot=None,\n","              max_delta_step=None, max_depth=5, max_leaves=None,\n","              min_child_weight=None, missing=nan, monotone_constraints=None,\n","              n_estimadors=400, n_estimators=100, n_jobs=None,\n","              num_parallel_tree=None, predictor=None, ...)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">XGBClassifier</label><div class=\"sk-toggleable__content\"><pre>XGBClassifier(base_score=None, booster=None, callbacks=None,\n","              colsample_bylevel=None, colsample_bynode=None,\n","              colsample_bytree=0.5506296722490095, early_stopping_rounds=None,\n","              enable_categorical=False, eval_metric=None, feature_types=None,\n","              gamma=0.7566166783103027, gpu_id=None, grow_policy=None,\n","              importance_type=None, interaction_constraints=None,\n","              learning_rate=0.0015383461504392903, max_bin=None,\n","              max_cat_threshold=None, max_cat_to_onehot=None,\n","              max_delta_step=None, max_depth=5, max_leaves=None,\n","              min_child_weight=None, missing=nan, monotone_constraints=None,\n","              n_estimadors=400, n_estimators=100, n_jobs=None,\n","              num_parallel_tree=None, predictor=None, ...)</pre></div></div></div></div></div>"],"text/plain":["XGBClassifier(base_score=None, booster=None, callbacks=None,\n","              colsample_bylevel=None, colsample_bynode=None,\n","              colsample_bytree=0.5506296722490095, early_stopping_rounds=None,\n","              enable_categorical=False, eval_metric=None, feature_types=None,\n","              gamma=0.7566166783103027, gpu_id=None, grow_policy=None,\n","              importance_type=None, interaction_constraints=None,\n","              learning_rate=0.0015383461504392903, max_bin=None,\n","              max_cat_threshold=None, max_cat_to_onehot=None,\n","              max_delta_step=None, max_depth=5, max_leaves=None,\n","              min_child_weight=None, missing=nan, monotone_constraints=None,\n","              n_estimadors=400, n_estimators=100, n_jobs=None,\n","              num_parallel_tree=None, predictor=None, ...)"]},"execution_count":9,"metadata":{},"output_type":"execute_result"}],"source":["best_xgb = xgb.XGBClassifier(n_estimadors = 400,\n","                            max_depth = 5,\n","                            learning_rate = 0.0015383461504392903,\n","                            subsample = 0.8714696835501025,\n","                            colsample_bytree = 0.5506296722490095,\n","                            gamma = 0.7566166783103027)\n","best_xgb.fit(X,y)"]},{"cell_type":"code","execution_count":10,"id":"a825e64e","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:03:33.695298Z","iopub.status.busy":"2023-08-01T22:03:33.694923Z","iopub.status.idle":"2023-08-01T22:03:33.738644Z","shell.execute_reply":"2023-08-01T22:03:33.737599Z"},"papermill":{"duration":0.066776,"end_time":"2023-08-01T22:03:33.740822","exception":false,"start_time":"2023-08-01T22:03:33.674046","status":"completed"},"tags":[]},"outputs":[{"data":{"text/html":["<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>AB</th>\n","      <th>AF</th>\n","      <th>AH</th>\n","      <th>AM</th>\n","      <th>AR</th>\n","      <th>AX</th>\n","      <th>AY</th>\n","      <th>AZ</th>\n","      <th>BC</th>\n","      <th>BD</th>\n","      <th>...</th>\n","      <th>FI</th>\n","      <th>FL</th>\n","      <th>FR</th>\n","      <th>FS</th>\n","      <th>GB</th>\n","      <th>GE</th>\n","      <th>GF</th>\n","      <th>GH</th>\n","      <th>GI</th>\n","      <th>GL</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>...</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>...</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>...</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>...</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>...</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5 rows × 56 columns</p>\n","</div>"],"text/plain":["    AB   AF   AH   AM   AR   AX   AY   AZ   BC  BD   ...   FI   FL   FR   FS  \\\n","0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0   \n","1  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0   \n","2  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0   \n","3  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0   \n","4  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  ...  0.0  0.0  0.0  0.0   \n","\n","    GB   GE   GF   GH   GI   GL  \n","0  0.0  0.0  0.0  0.0  0.0  0.0  \n","1  0.0  0.0  0.0  0.0  0.0  0.0  \n","2  0.0  0.0  0.0  0.0  0.0  0.0  \n","3  0.0  0.0  0.0  0.0  0.0  0.0  \n","4  0.0  0.0  0.0  0.0  0.0  0.0  \n","\n","[5 rows x 56 columns]"]},"execution_count":10,"metadata":{},"output_type":"execute_result"}],"source":["pred = test.copy()\n","pred.drop('Id',axis = 1,inplace=True)\n","pred.head()"]},{"cell_type":"code","execution_count":11,"id":"a736b737","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:03:33.782647Z","iopub.status.busy":"2023-08-01T22:03:33.782212Z","iopub.status.idle":"2023-08-01T22:03:33.797131Z","shell.execute_reply":"2023-08-01T22:03:33.796076Z"},"papermill":{"duration":0.038861,"end_time":"2023-08-01T22:03:33.799516","exception":false,"start_time":"2023-08-01T22:03:33.760655","status":"completed"},"tags":[]},"outputs":[],"source":["y_pred = best_xgb.predict_proba(pred)"]},{"cell_type":"code","execution_count":12,"id":"aa386e20","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:03:33.842783Z","iopub.status.busy":"2023-08-01T22:03:33.841826Z","iopub.status.idle":"2023-08-01T22:03:33.854529Z","shell.execute_reply":"2023-08-01T22:03:33.85353Z"},"papermill":{"duration":0.035754,"end_time":"2023-08-01T22:03:33.856702","exception":false,"start_time":"2023-08-01T22:03:33.820948","status":"completed"},"tags":[]},"outputs":[{"data":{"text/html":["<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>class_0</th>\n","      <th>class_1</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>00eed32682bb</td>\n","      <td>0.514287</td>\n","      <td>0.485713</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>010ebe33f668</td>\n","      <td>0.514287</td>\n","      <td>0.485713</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>02fa521e1838</td>\n","      <td>0.514287</td>\n","      <td>0.485713</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>040e15f562a2</td>\n","      <td>0.514287</td>\n","      <td>0.485713</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>046e85c7cc7f</td>\n","      <td>0.514287</td>\n","      <td>0.485713</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["             Id   class_0   class_1\n","0  00eed32682bb  0.514287  0.485713\n","1  010ebe33f668  0.514287  0.485713\n","2  02fa521e1838  0.514287  0.485713\n","3  040e15f562a2  0.514287  0.485713\n","4  046e85c7cc7f  0.514287  0.485713"]},"execution_count":12,"metadata":{},"output_type":"execute_result"}],"source":["submit = pd.DataFrame(y_pred,columns=['class_0','class_1'])\n","submit['Id'] = test[\"Id\"]\n","submit.reindex(columns=['Id','class_0','class_1'])"]},{"cell_type":"code","execution_count":13,"id":"54f14511","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:03:33.898933Z","iopub.status.busy":"2023-08-01T22:03:33.898511Z","iopub.status.idle":"2023-08-01T22:03:33.906276Z","shell.execute_reply":"2023-08-01T22:03:33.905291Z"},"papermill":{"duration":0.031427,"end_time":"2023-08-01T22:03:33.908459","exception":false,"start_time":"2023-08-01T22:03:33.877032","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["'from imblearn.under_sampling import RandomUnderSampler\\nimport numpy as np\\nfrom sklearn.metrics import log_loss\\nfrom sklearn.model_selection import KFold\\nimport optuna.integration.lightgbm as lgb\\nimport optuna\\nimport pandas as pd\\nimport numpy as np\\nfrom sklearn.datasets import make_classification\\nfrom sklearn.model_selection import train_test_split\\nfrom sklearn.metrics import roc_auc_score\\nfrom xgboost import XGBClassifier\\nfrom sklearn.ensemble import RandomForestClassifier\\nfrom imblearn.under_sampling import RandomUnderSampler\\n\\n\\n\\n\\nparams = {\\n    \\'boosting_type\\': \\'GBDT\\',\\n    \\'objective\\':\"binary\",\\n    \\'metric\\':\\'binary_logloss\\',\\n    \\'random_state\\': 42,\\n}\\n\\n\\n\\nfor i in range(20):\\n    \\n    positive_count_train = y.value_counts()[1]    \\n    sampler = RandomUnderSampler(sampling_strategy={0: positive_count_train, 1: positive_count_train},random_state=i, replacement=True)\\n    X_re, y_re = sampler.fit_resample(X, y)\\n\\n    (X_train, X_val , y_train , y_val) = train_test_split(X_re, y_re , test_size = 0.2,random_state=42)\\n    lgb_eval = lgb.Dataset(X_val.drop(\"Id\",axis=1), y_val,free_raw_data=False) \\n    lgb_train = lgb.Dataset(X_re.drop(\"Id\",axis=1), y_re,free_raw_data=False)         \\n    model = lgb.train(params, lgb_train, valid_sets=lgb_eval,\\n                      categorical_feature = categorical_features,\\n                      num_boost_round=1000,\\n                      early_stopping_rounds=20,\\n                      verbose_eval=10)\\n    \\n    pred = model.predict(X_test.drop(\"Id\",axis=1),num_iteration=model.best_iteration)\\n\\n    if i == 0:\\n        output = pd.DataFrame(pred, columns=[\\'pred\\' + str(i + 1)])\\n        output2 = output\\n    else:\\n        output = pd.DataFrame(pred, columns=[\\'pred\\' + str(i + 1)])\\n        output2 = pd.concat([output2, output], axis=1)\\n\\n'"]},"execution_count":13,"metadata":{},"output_type":"execute_result"}],"source":["'''from imblearn.under_sampling import RandomUnderSampler\n","import numpy as np\n","from sklearn.metrics import log_loss\n","from sklearn.model_selection import KFold\n","import optuna.integration.lightgbm as lgb\n","import optuna\n","import pandas as pd\n","import numpy as np\n","from sklearn.datasets import make_classification\n","from sklearn.model_selection import train_test_split\n","from sklearn.metrics import roc_auc_score\n","from xgboost import XGBClassifier\n","from sklearn.ensemble import RandomForestClassifier\n","from imblearn.under_sampling import RandomUnderSampler\n","\n","\n","\n","\n","params = {\n","    'boosting_type': 'GBDT',\n","    'objective':\"binary\",\n","    'metric':'binary_logloss',\n","    'random_state': 42,\n","}\n","\n","\n","\n","for i in range(20):\n","    \n","    positive_count_train = y.value_counts()[1]    \n","    sampler = RandomUnderSampler(sampling_strategy={0: positive_count_train, 1: positive_count_train},random_state=i, replacement=True)\n","    X_re, y_re = sampler.fit_resample(X, y)\n","\n","    (X_train, X_val , y_train , y_val) = train_test_split(X_re, y_re , test_size = 0.2,random_state=42)\n","    lgb_eval = lgb.Dataset(X_val.drop(\"Id\",axis=1), y_val,free_raw_data=False) \n","    lgb_train = lgb.Dataset(X_re.drop(\"Id\",axis=1), y_re,free_raw_data=False)         \n","    model = lgb.train(params, lgb_train, valid_sets=lgb_eval,\n","                      categorical_feature = categorical_features,\n","                      num_boost_round=1000,\n","                      early_stopping_rounds=20,\n","                      verbose_eval=10)\n","    \n","    pred = model.predict(X_test.drop(\"Id\",axis=1),num_iteration=model.best_iteration)\n","\n","    if i == 0:\n","        output = pd.DataFrame(pred, columns=['pred' + str(i + 1)])\n","        output2 = output\n","    else:\n","        output = pd.DataFrame(pred, columns=['pred' + str(i + 1)])\n","        output2 = pd.concat([output2, output], axis=1)\n","\n","'''"]},{"cell_type":"code","execution_count":14,"id":"4b528248","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:03:33.950914Z","iopub.status.busy":"2023-08-01T22:03:33.950537Z","iopub.status.idle":"2023-08-01T22:03:33.956387Z","shell.execute_reply":"2023-08-01T22:03:33.955445Z"},"papermill":{"duration":0.029736,"end_time":"2023-08-01T22:03:33.958456","exception":false,"start_time":"2023-08-01T22:03:33.92872","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["\"pred = output2.mean(axis='columns')\""]},"execution_count":14,"metadata":{},"output_type":"execute_result"}],"source":["'''pred = output2.mean(axis='columns')'''"]},{"cell_type":"code","execution_count":15,"id":"bfef28fb","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:03:34.001518Z","iopub.status.busy":"2023-08-01T22:03:34.000795Z","iopub.status.idle":"2023-08-01T22:03:34.005875Z","shell.execute_reply":"2023-08-01T22:03:34.005206Z"},"papermill":{"duration":0.028671,"end_time":"2023-08-01T22:03:34.0077","exception":false,"start_time":"2023-08-01T22:03:33.979029","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["'submit=pd.DataFrame(test_df[\"Id\"], columns=[\"Id\"])'"]},"execution_count":15,"metadata":{},"output_type":"execute_result"}],"source":["'''submit=pd.DataFrame(test_df[\"Id\"], columns=[\"Id\"])'''"]},{"cell_type":"code","execution_count":16,"id":"96359373","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:03:34.050516Z","iopub.status.busy":"2023-08-01T22:03:34.049799Z","iopub.status.idle":"2023-08-01T22:03:34.055245Z","shell.execute_reply":"2023-08-01T22:03:34.054324Z"},"papermill":{"duration":0.028997,"end_time":"2023-08-01T22:03:34.057128","exception":false,"start_time":"2023-08-01T22:03:34.028131","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["'submit[\"class_0\"]=1-pred\\nsubmit[\"class_1\"]=pred'"]},"execution_count":16,"metadata":{},"output_type":"execute_result"}],"source":["'''submit[\"class_0\"]=1-pred\n","submit[\"class_1\"]=pred'''"]},{"cell_type":"code","execution_count":17,"id":"79ea4125","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:03:34.100652Z","iopub.status.busy":"2023-08-01T22:03:34.099934Z","iopub.status.idle":"2023-08-01T22:03:34.110197Z","shell.execute_reply":"2023-08-01T22:03:34.109107Z"},"papermill":{"duration":0.034597,"end_time":"2023-08-01T22:03:34.112628","exception":false,"start_time":"2023-08-01T22:03:34.078031","status":"completed"},"tags":[]},"outputs":[],"source":["submit.to_csv('submission.csv',index=False)"]},{"cell_type":"code","execution_count":18,"id":"6c680954","metadata":{"execution":{"iopub.execute_input":"2023-08-01T22:03:34.156311Z","iopub.status.busy":"2023-08-01T22:03:34.155143Z","iopub.status.idle":"2023-08-01T22:03:34.165842Z","shell.execute_reply":"2023-08-01T22:03:34.164911Z"},"papermill":{"duration":0.034662,"end_time":"2023-08-01T22:03:34.16787","exception":false,"start_time":"2023-08-01T22:03:34.133208","status":"completed"},"tags":[]},"outputs":[{"data":{"text/html":["<div>\n","<style 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<td>0.485713</td>\n","      <td>040e15f562a2</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0.514287</td>\n","      <td>0.485713</td>\n","      <td>046e85c7cc7f</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["    class_0   class_1            Id\n","0  0.514287  0.485713  00eed32682bb\n","1  0.514287  0.485713  010ebe33f668\n","2  0.514287  0.485713  02fa521e1838\n","3  0.514287  0.485713  040e15f562a2\n","4  0.514287  0.485713  046e85c7cc7f"]},"execution_count":18,"metadata":{},"output_type":"execute_result"}],"source":["submit"]},{"cell_type":"code","execution_count":null,"id":"7a469ae5","metadata":{"papermill":{"duration":0.020363,"end_time":"2023-08-01T22:03:34.208787","exception":false,"start_time":"2023-08-01T22:03:34.188424","status":"completed"},"tags":[]},"outputs":[],"source":[]}],"metadata":{"kernelspec":{"display_name":"Python 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