removing-features-undersampling-optuna-xgb.ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":52784,"databundleVersionId":5687476,"sourceType":"competition"}],"dockerImageVersionId":30527,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import pandas as pd\nimport numpy as np","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2023-08-07T10:24:24.567455Z","iopub.execute_input":"2023-08-07T10:24:24.567910Z","iopub.status.idle":"2023-08-07T10:24:24.602087Z","shell.execute_reply.started":"2023-08-07T10:24:24.567876Z","shell.execute_reply":"2023-08-07T10:24:24.600957Z"},"trusted":true},"execution_count":1,"outputs":[]},{"cell_type":"code","source":"df=pd.read_csv(\"/kaggle/input/icr-identify-age-related-conditions/train.csv\")\nval=pd.read_csv(\"/kaggle/input/icr-identify-age-related-conditions/test.csv\")\nsub=pd.read_csv(\"/kaggle/input/icr-identify-age-related-conditions/sample_submission.csv\")","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:24:24.603939Z","iopub.execute_input":"2023-08-07T10:24:24.604609Z","iopub.status.idle":"2023-08-07T10:24:24.658986Z","shell.execute_reply.started":"2023-08-07T10:24:24.604572Z","shell.execute_reply":"2023-08-07T10:24:24.657752Z"},"trusted":true},"execution_count":2,"outputs":[]},{"cell_type":"code","source":"#df=df.drop(['AX', 'AY', 'AZ', 'BR', 'CB', 'CF', 'CW ', 'DN', 'EG', 'EL', 'EU', 'FC', 'FS', 'GB', 'GH', 'GI', 'Id'], axis =1 )\n\n#val=val.drop(['AX', 'AY', 'AZ', 'BR', 'CB', 'CF', 'CW ', 'DN', 'EG', 'EL', 'EU', 'FC', 'FS', 'GB', 'GH', 'GI', 'Id'], axis =1 )\n","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:24:24.660585Z","iopub.execute_input":"2023-08-07T10:24:24.661231Z","iopub.status.idle":"2023-08-07T10:24:24.666393Z","shell.execute_reply.started":"2023-08-07T10:24:24.661197Z","shell.execute_reply":"2023-08-07T10:24:24.665083Z"},"trusted":true},"execution_count":3,"outputs":[]},{"cell_type":"code","source":"zero, one =np.bincount(df['Class'])","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:24:24.669967Z","iopub.execute_input":"2023-08-07T10:24:24.670364Z","iopub.status.idle":"2023-08-07T10:24:24.685557Z","shell.execute_reply.started":"2023-08-07T10:24:24.670332Z","shell.execute_reply":"2023-08-07T10:24:24.684345Z"},"trusted":true},"execution_count":4,"outputs":[]},{"cell_type":"code","source":"zero_df=df.loc[df['Class']==0]\none_df=df.loc[df['Class']==1]","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:24:24.687302Z","iopub.execute_input":"2023-08-07T10:24:24.687701Z","iopub.status.idle":"2023-08-07T10:24:24.708120Z","shell.execute_reply.started":"2023-08-07T10:24:24.687666Z","shell.execute_reply":"2023-08-07T10:24:24.706564Z"},"trusted":true},"execution_count":5,"outputs":[]},{"cell_type":"code","source":"zero_df=zero_df.dropna()\nzero_df.shape","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:24:24.711055Z","iopub.execute_input":"2023-08-07T10:24:24.711558Z","iopub.status.idle":"2023-08-07T10:24:24.725791Z","shell.execute_reply.started":"2023-08-07T10:24:24.711508Z","shell.execute_reply":"2023-08-07T10:24:24.723803Z"},"trusted":true},"execution_count":6,"outputs":[{"execution_count":6,"output_type":"execute_result","data":{"text/plain":"(446, 58)"},"metadata":{}}]},{"cell_type":"code","source":"one_df=one_df.fillna(df.median())\nzero_df=zero_df.fillna(df.median())","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:24:24.727814Z","iopub.execute_input":"2023-08-07T10:24:24.728357Z","iopub.status.idle":"2023-08-07T10:24:24.793797Z","shell.execute_reply.started":"2023-08-07T10:24:24.728298Z","shell.execute_reply":"2023-08-07T10:24:24.792245Z"},"trusted":true},"execution_count":7,"outputs":[{"name":"stderr","text":"/tmp/ipykernel_32/3900790800.py:1: FutureWarning: The default value of numeric_only in DataFrame.median is deprecated. In a future version, it will default to False. In addition, specifying 'numeric_only=None' is deprecated. Select only valid columns or specify the value of numeric_only to silence this warning.\n  one_df=one_df.fillna(df.median())\n/tmp/ipykernel_32/3900790800.py:2: FutureWarning: The default value of numeric_only in DataFrame.median is deprecated. In a future version, it will default to False. In addition, specifying 'numeric_only=None' is deprecated. Select only valid columns or specify the value of numeric_only to silence this warning.\n  zero_df=zero_df.fillna(df.median())\n","output_type":"stream"}]},{"cell_type":"code","source":"zero_df=zero_df.drop(zero_df.sample(106).index)#","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:24:24.795478Z","iopub.execute_input":"2023-08-07T10:24:24.795868Z","iopub.status.idle":"2023-08-07T10:24:24.808385Z","shell.execute_reply.started":"2023-08-07T10:24:24.795836Z","shell.execute_reply":"2023-08-07T10:24:24.806941Z"},"trusted":true},"execution_count":8,"outputs":[]},{"cell_type":"code","source":"zero_df.shape","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:24:24.810203Z","iopub.execute_input":"2023-08-07T10:24:24.810670Z","iopub.status.idle":"2023-08-07T10:24:24.820583Z","shell.execute_reply.started":"2023-08-07T10:24:24.810612Z","shell.execute_reply":"2023-08-07T10:24:24.818987Z"},"trusted":true},"execution_count":9,"outputs":[{"execution_count":9,"output_type":"execute_result","data":{"text/plain":"(340, 58)"},"metadata":{}}]},{"cell_type":"code","source":"data=pd.concat([one_df,zero_df])","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:24:24.825561Z","iopub.execute_input":"2023-08-07T10:24:24.826036Z","iopub.status.idle":"2023-08-07T10:24:24.846875Z","shell.execute_reply.started":"2023-08-07T10:24:24.826000Z","shell.execute_reply":"2023-08-07T10:24:24.845693Z"},"trusted":true},"execution_count":10,"outputs":[]},{"cell_type":"code","source":"data=data.sample(frac=1,random_state=42)\ndata = data.reset_index(drop=True)\n#data=df\n#data=data.fillna(data.median())","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:24:24.848533Z","iopub.execute_input":"2023-08-07T10:24:24.849003Z","iopub.status.idle":"2023-08-07T10:24:24.859258Z","shell.execute_reply.started":"2023-08-07T10:24:24.848963Z","shell.execute_reply":"2023-08-07T10:24:24.857329Z"},"trusted":true},"execution_count":11,"outputs":[]},{"cell_type":"code","source":"from sklearn.preprocessing import LabelEncoder\n\ndata['EJ'] = LabelEncoder().fit_transform(data['EJ'])\ndata=data.drop(['Id'], axis=1)","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:24:24.861434Z","iopub.execute_input":"2023-08-07T10:24:24.862209Z","iopub.status.idle":"2023-08-07T10:24:25.495589Z","shell.execute_reply.started":"2023-08-07T10:24:24.862164Z","shell.execute_reply":"2023-08-07T10:24:25.494493Z"},"trusted":true},"execution_count":12,"outputs":[{"name":"stderr","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","output_type":"stream"}]},{"cell_type":"code","source":"val['EJ'] = LabelEncoder().fit_transform(val['EJ'])\nval=val.drop(['Id'], axis=1)","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:24:25.496907Z","iopub.execute_input":"2023-08-07T10:24:25.497229Z","iopub.status.idle":"2023-08-07T10:24:25.504529Z","shell.execute_reply.started":"2023-08-07T10:24:25.497202Z","shell.execute_reply":"2023-08-07T10:24:25.503213Z"},"trusted":true},"execution_count":13,"outputs":[]},{"cell_type":"code","source":"X=data.drop([\"Class\"], axis=1)\ny=data[\"Class\"]","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:24:25.506112Z","iopub.execute_input":"2023-08-07T10:24:25.506689Z","iopub.status.idle":"2023-08-07T10:24:25.522413Z","shell.execute_reply.started":"2023-08-07T10:24:25.506603Z","shell.execute_reply":"2023-08-07T10:24:25.520703Z"},"trusted":true},"execution_count":14,"outputs":[]},{"cell_type":"code","source":"'''def competition_log_loss(y_true, y_pred):\n    # y_true: correct labels 0, 1\n    # y_pred: predicted probabilities of class=1\n    #y_pred = y_pred.T[1]\n    N_0 = np.sum(1 - y_true)\n    N_1 = np.sum(y_true)\n    w_0 = (N_0 + N_1) / N_0\n    w_1 = (N_0 + N_1) / N_1\n    # Calculate the predicted probabilities for each class\n    p_1 = np.clip(y_pred, 1e-15, 1 - 1e-15)\n    p_0 = 1 - p_1\n    # Calculate the average log loss for each class\n    sum_0 = -np.sum((1 - y_true) * np.log(p_0))\n    sum_1 = -np.sum(y_true * np.log(p_1))\n    to_output = ((w_0 / N_0) * sum_0 + (w_1 / N_1) * sum_1) / (w_0 + w_1)\n\n    return to_output '''","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:24:25.524582Z","iopub.execute_input":"2023-08-07T10:24:25.525349Z","iopub.status.idle":"2023-08-07T10:24:25.543354Z","shell.execute_reply.started":"2023-08-07T10:24:25.525293Z","shell.execute_reply":"2023-08-07T10:24:25.541995Z"},"trusted":true},"execution_count":15,"outputs":[{"execution_count":15,"output_type":"execute_result","data":{"text/plain":"'def competition_log_loss(y_true, y_pred):\\n    # y_true: correct labels 0, 1\\n    # y_pred: predicted probabilities of class=1\\n    #y_pred = y_pred.T[1]\\n    N_0 = np.sum(1 - y_true)\\n    N_1 = np.sum(y_true)\\n    w_0 = (N_0 + N_1) / N_0\\n    w_1 = (N_0 + N_1) / N_1\\n    # Calculate the predicted probabilities for each class\\n    p_1 = np.clip(y_pred, 1e-15, 1 - 1e-15)\\n    p_0 = 1 - p_1\\n    # Calculate the average log loss for each class\\n    sum_0 = -np.sum((1 - y_true) * np.log(p_0))\\n    sum_1 = -np.sum(y_true * np.log(p_1))\\n    to_output = ((w_0 / N_0) * sum_0 + (w_1 / N_1) * sum_1) / (w_0 + w_1)\\n\\n    return to_output '"},"metadata":{}}]},{"cell_type":"code","source":"def competition_log_loss(y_true, y_pred):\n    N_0 = np.sum(1 - y_true)\n    N_1 = np.sum(y_true)\n    # calculate the weights for each class to balance classes\n    w_0 = 1 / N_0\n    w_1 = 1 / N_1\n    # calculate the predicted probabilities for each class\n    p_1 = np.clip(y_pred, 1e-15, 1 - 1e-15)\n    p_0 = 1 - p_1\n    # calculate the summed log loss for each class\n    log_loss_0 = -np.sum((1 - y_true) * np.log(p_0))\n    log_loss_1 = -np.sum(y_true * np.log(p_1))\n    # calculate the weighted summed logarithmic loss\n    balanced_log_loss = (w_0 * log_loss_0 + w_1 * log_loss_1) / 2\n    # return the average log loss\n    return balanced_log_loss","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:24:25.545596Z","iopub.execute_input":"2023-08-07T10:24:25.546107Z","iopub.status.idle":"2023-08-07T10:24:25.558027Z","shell.execute_reply.started":"2023-08-07T10:24:25.546063Z","shell.execute_reply":"2023-08-07T10:24:25.556594Z"},"trusted":true},"execution_count":16,"outputs":[]},{"cell_type":"code","source":"from IPython.display import display\nimport optuna\nfrom xgboost import XGBClassifier\nfrom sklearn.model_selection import KFold\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import roc_auc_score\nimport xgboost as xgb\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.metrics import make_scorer\nfrom sklearn.model_selection import StratifiedKFold\n\n\n\n\ndef obj_xgb(trial, X,y):\n    x_train, x_valid, y_train, y_valid = train_test_split(X, y, test_size=0.15, random_state=1021)\n\n    params = {\n        'n_estimators': trial.suggest_int('n_estimators', 50, 1000, step=50),\n        'max_depth': trial.suggest_int('max_depth', 3, 10),\n        'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\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, 0.2),\n        'objective': 'binary:logistic', \n        'eval_metric': 'logloss', \n    }\n\n    custom_scorer = make_scorer(competition_log_loss, greater_is_better=False)\n    model = xgb.XGBClassifier(**params)\n    \n    cv = StratifiedKFold(n_splits=5, shuffle=True)\n    \n    cv_scores = np.empty(5)\n    for idx, (train_idx, test_idx) in enumerate(cv.split(X, y)):\n        X_train, X_test = X.iloc[train_idx], X.iloc[test_idx]\n        y_train, y_test = y[train_idx], y[test_idx]\n        model.fit(X_train,y_train)\n        preds = model.predict_proba(X_test)[:,1]\n        #scores = cross_val_score(model, x, y, cv=kf,scoring=custom_scorer)\n        cv_scores[idx] = competition_log_loss(y_test, preds)\n \n        avg=cv_scores.mean()\n\n    \n    #y_pred = model.predict_proba(x_valid)[:, 1]\n    \n\n    #roc_auc = roc_auc_score(y_valid, y_pred)\n    \n    return avg\n    \n\n\nstudy = optuna.create_study(direction='minimize')\nstudy.optimize(lambda trial: obj_xgb(trial, X, y), n_trials=100)  # Pass X and y to the obj_xgb function\n\n\ndisplay(study)\n\nprint('Best trial:', study.best_trial.params)\nprint('Best clogloss:', study.best_trial.value)","metadata":{"_kg_hide-output":true,"scrolled":true,"execution":{"iopub.status.busy":"2023-08-07T10:24:25.560519Z","iopub.execute_input":"2023-08-07T10:24:25.562168Z","iopub.status.idle":"2023-08-07T10:29:24.146330Z","shell.execute_reply.started":"2023-08-07T10:24:25.562104Z","shell.execute_reply":"2023-08-07T10:29:24.145421Z"},"trusted":true},"execution_count":17,"outputs":[{"name":"stderr","text":"[I 2023-08-07 10:24:26,641] A new study created in memory with name: no-name-6c75075d-53bf-4ec0-8bd1-7dc900c1c619\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:24:28,168] Trial 0 finished with value: 0.36082815084908276 and parameters: {'n_estimators': 300, 'max_depth': 8, 'learning_rate': 0.15953224602512492, 'subsample': 0.9776139082531522, 'colsample_bytree': 0.6561022968299389, 'gamma': 0.03353026903527989}. Best is trial 0 with value: 0.36082815084908276.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:24:28,728] Trial 1 finished with value: 0.35313985325733743 and parameters: {'n_estimators': 100, 'max_depth': 3, 'learning_rate': 0.2190886542698704, 'subsample': 0.5646160093419837, 'colsample_bytree': 0.685280416919874, 'gamma': 0.06450755438710412}. Best is trial 1 with value: 0.35313985325733743.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:24:30,400] Trial 2 finished with value: 0.33356472266091014 and parameters: {'n_estimators': 400, 'max_depth': 6, 'learning_rate': 0.28189576904592756, 'subsample': 0.5902160056795427, 'colsample_bytree': 0.625003358758465, 'gamma': 0.023954893143495064}. Best is trial 2 with value: 0.33356472266091014.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:24:34,110] Trial 3 finished with value: 0.40626275974827675 and parameters: {'n_estimators': 950, 'max_depth': 5, 'learning_rate': 0.45766903430896516, 'subsample': 0.6434127095832426, 'colsample_bytree': 0.8397783141405714, 'gamma': 0.1426178857765842}. Best is trial 2 with value: 0.33356472266091014.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:24:37,996] Trial 4 finished with value: 0.3407164284469541 and parameters: {'n_estimators': 600, 'max_depth': 6, 'learning_rate': 0.14015566606708738, 'subsample': 0.6532131045323644, 'colsample_bytree': 0.9063982189767815, 'gamma': 0.0248531969884022}. Best is trial 2 with value: 0.33356472266091014.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:24:39,956] Trial 5 finished with value: 0.3278467932217297 and parameters: {'n_estimators': 350, 'max_depth': 7, 'learning_rate': 0.1413104688566075, 'subsample': 0.6714075658347027, 'colsample_bytree': 0.8973383914518429, 'gamma': 0.007332592617513924}. Best is trial 5 with value: 0.3278467932217297.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:24:41,192] Trial 6 finished with value: 0.38636744889345714 and parameters: {'n_estimators': 300, 'max_depth': 8, 'learning_rate': 0.6278001484117786, 'subsample': 0.7371667487621348, 'colsample_bytree': 0.8140328244946222, 'gamma': 0.0113158641790906}. Best is trial 5 with value: 0.3278467932217297.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:24:45,319] Trial 7 finished with value: 0.3871880515766357 and parameters: {'n_estimators': 950, 'max_depth': 5, 'learning_rate': 0.19159481070168502, 'subsample': 0.7542348188059478, 'colsample_bytree': 0.9172648819095138, 'gamma': 0.10915044831274827}. Best is trial 5 with value: 0.3278467932217297.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:24:46,135] Trial 8 finished with value: 0.5448681956969953 and parameters: {'n_estimators': 200, 'max_depth': 5, 'learning_rate': 0.9462990656393309, 'subsample': 0.5537163961782481, 'colsample_bytree': 0.63074605107973, 'gamma': 0.010115553412356655}. Best is trial 5 with value: 0.3278467932217297.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:24:49,431] Trial 9 finished with value: 0.4733339705831505 and parameters: {'n_estimators': 950, 'max_depth': 5, 'learning_rate': 0.6238012099799498, 'subsample': 0.5507239360889199, 'colsample_bytree': 0.778574973702324, 'gamma': 0.001711000153906133}. Best is trial 5 with value: 0.3278467932217297.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:24:52,412] Trial 10 finished with value: 0.34630459535821123 and parameters: {'n_estimators': 600, 'max_depth': 10, 'learning_rate': 0.1063559756402729, 'subsample': 0.7649230446520686, 'colsample_bytree': 0.9860036797852132, 'gamma': 0.00413064573328856}. Best is trial 5 with value: 0.3278467932217297.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:24:54,136] Trial 11 finished with value: 0.3499930220460221 and parameters: {'n_estimators': 450, 'max_depth': 8, 'learning_rate': 0.2732671325037955, 'subsample': 0.5096062189251809, 'colsample_bytree': 0.501184157780392, 'gamma': 0.006211220823288593}. Best is trial 5 with value: 0.3278467932217297.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:24:55,925] Trial 12 finished with value: 0.35853060527399927 and parameters: {'n_estimators': 450, 'max_depth': 7, 'learning_rate': 0.2997844275572026, 'subsample': 0.6377796522965847, 'colsample_bytree': 0.7300338947556254, 'gamma': 0.018546478106848497}. Best is trial 5 with value: 0.3278467932217297.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:24:58,547] Trial 13 finished with value: 0.3801063412053953 and parameters: {'n_estimators': 700, 'max_depth': 10, 'learning_rate': 0.23385229742831296, 'subsample': 0.6680455986703083, 'colsample_bytree': 0.6012103469114584, 'gamma': 0.041909365181383}. Best is trial 5 with value: 0.3278467932217297.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:24:59,964] Trial 14 finished with value: 0.3754087819329923 and parameters: {'n_estimators': 300, 'max_depth': 7, 'learning_rate': 0.3633672608039155, 'subsample': 0.6024444888837774, 'colsample_bytree': 0.7383578306458412, 'gamma': 0.0035307973336702304}. Best is trial 5 with value: 0.3278467932217297.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:01,979] Trial 15 finished with value: 0.3097437852145036 and parameters: {'n_estimators': 450, 'max_depth': 3, 'learning_rate': 0.10244198117966895, 'subsample': 0.6932170317326048, 'colsample_bytree': 0.5762006082458462, 'gamma': 0.01666719229770812}. Best is trial 15 with value: 0.3097437852145036.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:05,286] Trial 16 finished with value: 0.31087287660347335 and parameters: {'n_estimators': 800, 'max_depth': 4, 'learning_rate': 0.10107997067600341, 'subsample': 0.7083631209394783, 'colsample_bytree': 0.5436328004622684, 'gamma': 0.013321583197976708}. Best is trial 15 with value: 0.3097437852145036.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:09,709] Trial 17 finished with value: 0.308184200661071 and parameters: {'n_estimators': 800, 'max_depth': 3, 'learning_rate': 0.10009952458798935, 'subsample': 0.8212839997604441, 'colsample_bytree': 0.5279492218191335, 'gamma': 0.015405099730731219}. Best is trial 17 with value: 0.308184200661071.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:12,674] Trial 18 finished with value: 0.30843519584909995 and parameters: {'n_estimators': 750, 'max_depth': 3, 'learning_rate': 0.12100295354662415, 'subsample': 0.8126036026273863, 'colsample_bytree': 0.5783670508818352, 'gamma': 0.017165037820630967}. Best is trial 17 with value: 0.308184200661071.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:15,902] Trial 19 finished with value: 0.32196015851613763 and parameters: {'n_estimators': 800, 'max_depth': 3, 'learning_rate': 0.12961213825860002, 'subsample': 0.8307236231855744, 'colsample_bytree': 0.5038260445356081, 'gamma': 0.04355481646650123}. Best is trial 17 with value: 0.308184200661071.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:19,139] Trial 20 finished with value: 0.3118601151904949 and parameters: {'n_estimators': 800, 'max_depth': 4, 'learning_rate': 0.173988227067807, 'subsample': 0.8538659462661877, 'colsample_bytree': 0.5620923018310683, 'gamma': 0.08168542516179594}. Best is trial 17 with value: 0.308184200661071.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:22,100] Trial 21 finished with value: 0.3265568768705949 and parameters: {'n_estimators': 700, 'max_depth': 3, 'learning_rate': 0.11451492541222819, 'subsample': 0.8174697699783338, 'colsample_bytree': 0.575448602325547, 'gamma': 0.017566619309536877}. Best is trial 17 with value: 0.308184200661071.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:24,516] Trial 22 finished with value: 0.29701671396174606 and parameters: {'n_estimators': 550, 'max_depth': 4, 'learning_rate': 0.10006488037134945, 'subsample': 0.8789574806491175, 'colsample_bytree': 0.5481702364441184, 'gamma': 0.014299443791650247}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:27,170] Trial 23 finished with value: 0.31372424493031914 and parameters: {'n_estimators': 650, 'max_depth': 4, 'learning_rate': 0.12753639591971364, 'subsample': 0.8894790719204773, 'colsample_bytree': 0.535629916126827, 'gamma': 0.027688421003077657}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:30,515] Trial 24 finished with value: 0.30260773561310617 and parameters: {'n_estimators': 850, 'max_depth': 4, 'learning_rate': 0.15714573330375067, 'subsample': 0.9014592412513497, 'colsample_bytree': 0.5942643657097683, 'gamma': 0.01349977111607983}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:33,708] Trial 25 finished with value: 0.3418978743361108 and parameters: {'n_estimators': 850, 'max_depth': 4, 'learning_rate': 0.15685990484642684, 'subsample': 0.9109556179651235, 'colsample_bytree': 0.530482295824054, 'gamma': 0.007131000214755804}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:36,524] Trial 26 finished with value: 0.3134027380619428 and parameters: {'n_estimators': 550, 'max_depth': 4, 'learning_rate': 0.10109823987846957, 'subsample': 0.9295739860647956, 'colsample_bytree': 0.6080840380322761, 'gamma': 0.19647624615188228}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:41,566] Trial 27 finished with value: 0.3626573700864061 and parameters: {'n_estimators': 1000, 'max_depth': 4, 'learning_rate': 0.13732717341228393, 'subsample': 0.8764088565280951, 'colsample_bytree': 0.6671826985829671, 'gamma': 0.014174826864298358}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:44,802] Trial 28 finished with value: 0.34488329938908674 and parameters: {'n_estimators': 850, 'max_depth': 6, 'learning_rate': 0.18673435905906674, 'subsample': 0.959738914789894, 'colsample_bytree': 0.500357743476793, 'gamma': 0.010039916125486773}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:48,512] Trial 29 finished with value: 0.30326428470589406 and parameters: {'n_estimators': 900, 'max_depth': 9, 'learning_rate': 0.16390474804541363, 'subsample': 0.9807874193923933, 'colsample_bytree': 0.6744629993603112, 'gamma': 0.037359433755473875}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:52,388] Trial 30 finished with value: 0.39065554639551336 and parameters: {'n_estimators': 900, 'max_depth': 9, 'learning_rate': 0.1655340854897989, 'subsample': 0.9842953670085126, 'colsample_bytree': 0.6941171382202038, 'gamma': 0.0355639930653342}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:25:56,539] Trial 31 finished with value: 0.33596931908542244 and parameters: {'n_estimators': 1000, 'max_depth': 9, 'learning_rate': 0.12116309668443397, 'subsample': 0.9480970432164365, 'colsample_bytree': 0.6464700461956537, 'gamma': 0.024713928587956048}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:00,314] Trial 32 finished with value: 0.3691388308553655 and parameters: {'n_estimators': 900, 'max_depth': 9, 'learning_rate': 0.15016581249633446, 'subsample': 0.979423217364823, 'colsample_bytree': 0.5982691754161091, 'gamma': 0.04873267924803995}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:00,743] Trial 33 finished with value: 0.3739248345773645 and parameters: {'n_estimators': 50, 'max_depth': 3, 'learning_rate': 0.2076110034600378, 'subsample': 0.9174116371675753, 'colsample_bytree': 0.6473549731928573, 'gamma': 0.060617282357064386}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:03,667] Trial 34 finished with value: 0.4010929758443723 and parameters: {'n_estimators': 700, 'max_depth': 5, 'learning_rate': 0.15943649056794104, 'subsample': 0.9994126708012967, 'colsample_bytree': 0.6262757211303267, 'gamma': 0.03424843560442391}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:04,941] Trial 35 finished with value: 0.33262347909863416 and parameters: {'n_estimators': 200, 'max_depth': 6, 'learning_rate': 0.11688618539023687, 'subsample': 0.9561513212717155, 'colsample_bytree': 0.6831167509415484, 'gamma': 0.024986897725820065}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:07,192] Trial 36 finished with value: 0.32148600984372366 and parameters: {'n_estimators': 550, 'max_depth': 3, 'learning_rate': 0.14115307366441382, 'subsample': 0.8813116797137562, 'colsample_bytree': 0.553227813857656, 'gamma': 0.022129652101989992}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:10,603] Trial 37 finished with value: 0.3411619123760131 and parameters: {'n_estimators': 850, 'max_depth': 4, 'learning_rate': 0.1770071602202005, 'subsample': 0.9330389967922804, 'colsample_bytree': 0.5958136313930029, 'gamma': 0.029703621701487787}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:14,721] Trial 38 finished with value: 0.36974373611319716 and parameters: {'n_estimators': 750, 'max_depth': 5, 'learning_rate': 0.11462360382598595, 'subsample': 0.8983143288033484, 'colsample_bytree': 0.5309039215922364, 'gamma': 0.011755765401429263}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:18,222] Trial 39 finished with value: 0.31804288681397896 and parameters: {'n_estimators': 900, 'max_depth': 8, 'learning_rate': 0.14755411887699493, 'subsample': 0.8625971084580276, 'colsample_bytree': 0.6203287732754352, 'gamma': 0.02205178234435385}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:20,754] Trial 40 finished with value: 0.3274605688094202 and parameters: {'n_estimators': 650, 'max_depth': 3, 'learning_rate': 0.2090794933975901, 'subsample': 0.9032639616763554, 'colsample_bytree': 0.5652483049526794, 'gamma': 0.008775146429526317}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:23,813] Trial 41 finished with value: 0.30854110476764524 and parameters: {'n_estimators': 800, 'max_depth': 3, 'learning_rate': 0.12806510223601703, 'subsample': 0.8264155257758063, 'colsample_bytree': 0.5805897631725806, 'gamma': 0.016052723513169363}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:26,769] Trial 42 finished with value: 0.34297896265379524 and parameters: {'n_estimators': 750, 'max_depth': 3, 'learning_rate': 0.11291043708109977, 'subsample': 0.8052801317485048, 'colsample_bytree': 0.5844407855156608, 'gamma': 0.012717597528167346}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:29,839] Trial 43 finished with value: 0.35532523217977036 and parameters: {'n_estimators': 750, 'max_depth': 4, 'learning_rate': 0.1328708207113566, 'subsample': 0.7824823373266959, 'colsample_bytree': 0.6195900447065862, 'gamma': 0.019331665116922966}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:33,651] Trial 44 finished with value: 0.3249818957502316 and parameters: {'n_estimators': 950, 'max_depth': 5, 'learning_rate': 0.11052179026173498, 'subsample': 0.8505914035098338, 'colsample_bytree': 0.5439968723082803, 'gamma': 0.03222805753243586}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:36,120] Trial 45 finished with value: 0.3739899896269592 and parameters: {'n_estimators': 600, 'max_depth': 3, 'learning_rate': 0.12276872691144866, 'subsample': 0.796339376627681, 'colsample_bytree': 0.5230148543919814, 'gamma': 0.014522948453903159}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:39,574] Trial 46 finished with value: 0.31642481979729714 and parameters: {'n_estimators': 900, 'max_depth': 5, 'learning_rate': 0.1508344617850162, 'subsample': 0.8404215390241739, 'colsample_bytree': 0.5632043464219947, 'gamma': 0.01909648858601588}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:41,891] Trial 47 finished with value: 0.3541652833052688 and parameters: {'n_estimators': 500, 'max_depth': 4, 'learning_rate': 0.10169303407790171, 'subsample': 0.8696654947953802, 'colsample_bytree': 0.6377745608650277, 'gamma': 0.009869007296451064}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:45,659] Trial 48 finished with value: 0.3335021206548572 and parameters: {'n_estimators': 650, 'max_depth': 10, 'learning_rate': 0.1330815652936955, 'subsample': 0.7770872182117877, 'colsample_bytree': 0.5919558918416398, 'gamma': 0.01264334503799254}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:47,330] Trial 49 finished with value: 0.3586872131042932 and parameters: {'n_estimators': 350, 'max_depth': 6, 'learning_rate': 0.16625734616247567, 'subsample': 0.7449234389101448, 'colsample_bytree': 0.6628571421002123, 'gamma': 0.007850070699745625}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:50,883] Trial 50 finished with value: 0.34562411275375216 and parameters: {'n_estimators': 850, 'max_depth': 7, 'learning_rate': 0.10931705211924224, 'subsample': 0.8366555593670365, 'colsample_bytree': 0.5561753879574076, 'gamma': 0.02007483457561169}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:54,075] Trial 51 finished with value: 0.29814117795602685 and parameters: {'n_estimators': 800, 'max_depth': 3, 'learning_rate': 0.1261740609073006, 'subsample': 0.8095129787621489, 'colsample_bytree': 0.6033428041178539, 'gamma': 0.015803067599471247}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:26:57,108] Trial 52 finished with value: 0.33564239024016523 and parameters: {'n_estimators': 750, 'max_depth': 3, 'learning_rate': 0.12094002271522619, 'subsample': 0.8035798389966843, 'colsample_bytree': 0.6073662365335388, 'gamma': 0.014927906954176203}. Best is trial 22 with value: 0.29701671396174606.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:01,022] Trial 53 finished with value: 0.29205542857313244 and parameters: {'n_estimators': 950, 'max_depth': 3, 'learning_rate': 0.10011082600730542, 'subsample': 0.8619595039995852, 'colsample_bytree': 0.520838075080526, 'gamma': 0.026323989823045096}. Best is trial 53 with value: 0.29205542857313244.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:04,866] Trial 54 finished with value: 0.32885000782470175 and parameters: {'n_estimators': 950, 'max_depth': 4, 'learning_rate': 0.10643764115992418, 'subsample': 0.8607155982824319, 'colsample_bytree': 0.5216346383777161, 'gamma': 0.026499143648268438}. Best is trial 53 with value: 0.29205542857313244.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:08,824] Trial 55 finished with value: 0.399257468786465 and parameters: {'n_estimators': 1000, 'max_depth': 3, 'learning_rate': 0.1408792475997382, 'subsample': 0.8944609647276753, 'colsample_bytree': 0.5154600328532295, 'gamma': 0.037863548610325655}. Best is trial 53 with value: 0.29205542857313244.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:12,687] Trial 56 finished with value: 0.3518272948807366 and parameters: {'n_estimators': 950, 'max_depth': 4, 'learning_rate': 0.10894760792198974, 'subsample': 0.8797021903869614, 'colsample_bytree': 0.5443448149262906, 'gamma': 0.010708524621376145}. Best is trial 53 with value: 0.29205542857313244.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:17,426] Trial 57 finished with value: 0.32263297020870935 and parameters: {'n_estimators': 900, 'max_depth': 3, 'learning_rate': 0.10019000969748217, 'subsample': 0.922057978307313, 'colsample_bytree': 0.5630614504279228, 'gamma': 0.029770917325988987}. Best is trial 53 with value: 0.29205542857313244.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:20,848] Trial 58 finished with value: 0.2917518513496538 and parameters: {'n_estimators': 850, 'max_depth': 4, 'learning_rate': 0.12836913677687362, 'subsample': 0.8480774658122153, 'colsample_bytree': 0.5404390500264756, 'gamma': 0.015775830815257547}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:24,053] Trial 59 finished with value: 0.3459248849915263 and parameters: {'n_estimators': 850, 'max_depth': 5, 'learning_rate': 0.14875456592105704, 'subsample': 0.8388684667633929, 'colsample_bytree': 0.514144034623809, 'gamma': 0.006236310015455396}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:25,192] Trial 60 finished with value: 0.33253574958361704 and parameters: {'n_estimators': 200, 'max_depth': 4, 'learning_rate': 0.13350341687860318, 'subsample': 0.9025110532742872, 'colsample_bytree': 0.6145953820750654, 'gamma': 0.023347731860323396}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:28,335] Trial 61 finished with value: 0.3343596702608201 and parameters: {'n_estimators': 800, 'max_depth': 4, 'learning_rate': 0.12391805167731682, 'subsample': 0.8532657247159888, 'colsample_bytree': 0.5809972160979978, 'gamma': 0.015983966978261047}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:32,237] Trial 62 finished with value: 0.34542675705353665 and parameters: {'n_estimators': 1000, 'max_depth': 3, 'learning_rate': 0.11385091113621162, 'subsample': 0.8219378246229492, 'colsample_bytree': 0.5404848788875316, 'gamma': 0.018304734653151702}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:35,408] Trial 63 finished with value: 0.29760894169771274 and parameters: {'n_estimators': 800, 'max_depth': 4, 'learning_rate': 0.10537418954866655, 'subsample': 0.8670599005514139, 'colsample_bytree': 0.5109352421043875, 'gamma': 0.0127294628592233}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:38,181] Trial 64 finished with value: 0.325264530244026 and parameters: {'n_estimators': 700, 'max_depth': 4, 'learning_rate': 0.13888176327399543, 'subsample': 0.8850730505363045, 'colsample_bytree': 0.5007717297732037, 'gamma': 0.011603845429666517}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:41,671] Trial 65 finished with value: 0.3329724348637515 and parameters: {'n_estimators': 850, 'max_depth': 5, 'learning_rate': 0.12442647777982467, 'subsample': 0.865122174468649, 'colsample_bytree': 0.5502645130220133, 'gamma': 0.0134170341504793}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:45,334] Trial 66 finished with value: 0.3440096246719639 and parameters: {'n_estimators': 900, 'max_depth': 7, 'learning_rate': 0.10919221140107428, 'subsample': 0.9349065068984859, 'colsample_bytree': 0.5163944441425516, 'gamma': 0.00921881285747547}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:50,295] Trial 67 finished with value: 0.32122440634409777 and parameters: {'n_estimators': 950, 'max_depth': 8, 'learning_rate': 0.1569813879121055, 'subsample': 0.916755075023635, 'colsample_bytree': 0.5328679982623459, 'gamma': 0.02142396262737291}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:53,334] Trial 68 finished with value: 0.3091559300603586 and parameters: {'n_estimators': 800, 'max_depth': 4, 'learning_rate': 0.18736544297604005, 'subsample': 0.8481131633080226, 'colsample_bytree': 0.597695736708768, 'gamma': 0.026228659306959685}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:55,250] Trial 69 finished with value: 0.376431250760725 and parameters: {'n_estimators': 400, 'max_depth': 5, 'learning_rate': 0.11940526956557633, 'subsample': 0.9618703303079773, 'colsample_bytree': 0.5690831798779068, 'gamma': 0.047285034497082726}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:27:59,007] Trial 70 finished with value: 0.3161592382488708 and parameters: {'n_estimators': 950, 'max_depth': 4, 'learning_rate': 0.1065241628427593, 'subsample': 0.8841634309037812, 'colsample_bytree': 0.550993966963227, 'gamma': 0.011510026816773745}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:02,396] Trial 71 finished with value: 0.3266237755689348 and parameters: {'n_estimators': 800, 'max_depth': 3, 'learning_rate': 0.1006725443353618, 'subsample': 0.8187788678882423, 'colsample_bytree': 0.5297685226915845, 'gamma': 0.01595539963901148}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:05,683] Trial 72 finished with value: 0.2993294429341057 and parameters: {'n_estimators': 850, 'max_depth': 3, 'learning_rate': 0.11459716770101702, 'subsample': 0.8362689419316621, 'colsample_bytree': 0.5086051086692236, 'gamma': 0.018044292197919046}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:08,896] Trial 73 finished with value: 0.33922308836843823 and parameters: {'n_estimators': 850, 'max_depth': 3, 'learning_rate': 0.13126360989585945, 'subsample': 0.8706091764564683, 'colsample_bytree': 0.5027302312777523, 'gamma': 0.01827126912184501}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:12,443] Trial 74 finished with value: 0.35481491286659217 and parameters: {'n_estimators': 900, 'max_depth': 4, 'learning_rate': 0.11824522340512826, 'subsample': 0.8343630430268254, 'colsample_bytree': 0.5735741463725424, 'gamma': 0.01374753523851589}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:15,263] Trial 75 finished with value: 0.33125899213045235 and parameters: {'n_estimators': 700, 'max_depth': 3, 'learning_rate': 0.11527692448074296, 'subsample': 0.907759236497829, 'colsample_bytree': 0.5160180611518861, 'gamma': 0.02140998051729716}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:19,771] Trial 76 finished with value: 0.3011793966588499 and parameters: {'n_estimators': 850, 'max_depth': 3, 'learning_rate': 0.14329900611403745, 'subsample': 0.8894718582536332, 'colsample_bytree': 0.540432479444812, 'gamma': 0.030344206087077625}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:22,882] Trial 77 finished with value: 0.2998407220108304 and parameters: {'n_estimators': 800, 'max_depth': 3, 'learning_rate': 0.14220222618874714, 'subsample': 0.8560350454753564, 'colsample_bytree': 0.5407047301757797, 'gamma': 0.028546111908022708}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:25,820] Trial 78 finished with value: 0.33477646569575087 and parameters: {'n_estimators': 750, 'max_depth': 3, 'learning_rate': 0.12541769034981806, 'subsample': 0.8549809461581034, 'colsample_bytree': 0.5341626758570918, 'gamma': 0.03160576730792184}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:28,908] Trial 79 finished with value: 0.3070794881261464 and parameters: {'n_estimators': 800, 'max_depth': 3, 'learning_rate': 0.14209611850226841, 'subsample': 0.8700360404433775, 'colsample_bytree': 0.5466436897696192, 'gamma': 0.026990178378387304}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:32,328] Trial 80 finished with value: 0.36204625077936525 and parameters: {'n_estimators': 850, 'max_depth': 3, 'learning_rate': 0.10530032369493808, 'subsample': 0.8426794518357253, 'colsample_bytree': 0.5212552525521531, 'gamma': 0.024464467892685336}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:35,630] Trial 81 finished with value: 0.33502727329466697 and parameters: {'n_estimators': 850, 'max_depth': 4, 'learning_rate': 0.13467844766368786, 'subsample': 0.8874087201856209, 'colsample_bytree': 0.5375199047858712, 'gamma': 0.017220137451580617}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:38,688] Trial 82 finished with value: 0.30765211334612197 and parameters: {'n_estimators': 750, 'max_depth': 3, 'learning_rate': 0.11294113245369797, 'subsample': 0.8271143996663682, 'colsample_bytree': 0.5597661753086245, 'gamma': 0.020563409987752624}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:42,249] Trial 83 finished with value: 0.3041410720388592 and parameters: {'n_estimators': 900, 'max_depth': 3, 'learning_rate': 0.12718843836270025, 'subsample': 0.895263479985105, 'colsample_bytree': 0.5063003004834131, 'gamma': 0.014530186127938181}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:45,464] Trial 84 finished with value: 0.29989998249436894 and parameters: {'n_estimators': 800, 'max_depth': 4, 'learning_rate': 0.14423680429488508, 'subsample': 0.8585550953657229, 'colsample_bytree': 0.5843610767105797, 'gamma': 0.01083761438087698}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:48,133] Trial 85 finished with value: 0.34841766079637876 and parameters: {'n_estimators': 650, 'max_depth': 3, 'learning_rate': 0.14993811439541677, 'subsample': 0.8589703336420278, 'colsample_bytree': 0.57142567324655, 'gamma': 0.011110256862978066}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:52,696] Trial 86 finished with value: 0.35154774077655304 and parameters: {'n_estimators': 800, 'max_depth': 4, 'learning_rate': 0.10596940372302563, 'subsample': 0.8127300809805438, 'colsample_bytree': 0.5527018105513157, 'gamma': 0.02988726719870796}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:55,703] Trial 87 finished with value: 0.34388932445056314 and parameters: {'n_estimators': 700, 'max_depth': 3, 'learning_rate': 0.11511195533483662, 'subsample': 0.8731146232836781, 'colsample_bytree': 0.5243660324057065, 'gamma': 0.016858785103585388}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:28:58,265] Trial 88 finished with value: 0.32626623506366953 and parameters: {'n_estimators': 600, 'max_depth': 4, 'learning_rate': 0.1431920885508552, 'subsample': 0.845919347224944, 'colsample_bytree': 0.5376489366517084, 'gamma': 0.023045688818791484}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:29:01,325] Trial 89 finished with value: 0.3730062909384941 and parameters: {'n_estimators': 800, 'max_depth': 3, 'learning_rate': 0.17381827489986032, 'subsample': 0.8299729475612014, 'colsample_bytree': 0.5840754786395015, 'gamma': 0.008852840806357171}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:29:04,257] Trial 90 finished with value: 0.32066299671834064 and parameters: {'n_estimators': 750, 'max_depth': 4, 'learning_rate': 0.12825650228707408, 'subsample': 0.79415406230257, 'colsample_bytree': 0.5138300685536804, 'gamma': 0.012612816980862708}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:29:07,536] Trial 91 finished with value: 0.34423183203305363 and parameters: {'n_estimators': 850, 'max_depth': 4, 'learning_rate': 0.15632781864762066, 'subsample': 0.8643382988994521, 'colsample_bytree': 0.5881606145654833, 'gamma': 0.009986133504317509}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:29:11,197] Trial 92 finished with value: 0.3503855322197652 and parameters: {'n_estimators': 900, 'max_depth': 3, 'learning_rate': 0.11967290264841754, 'subsample': 0.8775369310798874, 'colsample_bytree': 0.5611353425987621, 'gamma': 0.01925647595214361}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:29:14,335] Trial 93 finished with value: 0.3238304725016282 and parameters: {'n_estimators': 800, 'max_depth': 5, 'learning_rate': 0.13433008504736044, 'subsample': 0.8935423204177635, 'colsample_bytree': 0.5726867067927701, 'gamma': 0.014369536198204583}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:29:16,536] Trial 94 finished with value: 0.33266225451750164 and parameters: {'n_estimators': 500, 'max_depth': 4, 'learning_rate': 0.11015179015220418, 'subsample': 0.8507555192112052, 'colsample_bytree': 0.5501199841239928, 'gamma': 0.01210253780926086}. Best is trial 58 with value: 0.2917518513496538.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:29:17,815] Trial 95 finished with value: 0.28131809579227507 and parameters: {'n_estimators': 250, 'max_depth': 4, 'learning_rate': 0.14463868242527206, 'subsample': 0.9029714947424823, 'colsample_bytree': 0.5305435748830561, 'gamma': 0.015968888840893466}. Best is trial 95 with value: 0.28131809579227507.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:29:19,037] Trial 96 finished with value: 0.29394422672879156 and parameters: {'n_estimators': 250, 'max_depth': 3, 'learning_rate': 0.14611928425037932, 'subsample': 0.9066055420984198, 'colsample_bytree': 0.5284208455306721, 'gamma': 0.016885560983945794}. Best is trial 95 with value: 0.28131809579227507.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:29:20,489] Trial 97 finished with value: 0.3031043495796059 and parameters: {'n_estimators': 250, 'max_depth': 4, 'learning_rate': 0.10453499395560151, 'subsample': 0.9088051068954265, 'colsample_bytree': 0.5262116655377993, 'gamma': 0.01642652104193967}. Best is trial 95 with value: 0.28131809579227507.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:29:22,825] Trial 98 finished with value: 0.3174574991393545 and parameters: {'n_estimators': 250, 'max_depth': 3, 'learning_rate': 0.11940826476751053, 'subsample': 0.8383548170013745, 'colsample_bytree': 0.5099731215613218, 'gamma': 0.018197716064825852}. Best is trial 95 with value: 0.28131809579227507.\n/tmp/ipykernel_32/300164230.py:21: 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 suggest_float(..., log=True) instead.\n  'learning_rate': trial.suggest_loguniform('learning_rate', 0.1, 1.0),\n/tmp/ipykernel_32/300164230.py:22: 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 suggest_float instead.\n  'subsample': trial.suggest_uniform('subsample', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:23: 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 suggest_float instead.\n  'colsample_bytree': trial.suggest_uniform('colsample_bytree', 0.5, 1.0),\n/tmp/ipykernel_32/300164230.py:24: 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 suggest_float(..., log=True) instead.\n  'gamma': trial.suggest_loguniform('gamma', 0.001, 0.2),\n[I 2023-08-07 10:29:24,138] Trial 99 finished with value: 0.3355204443305076 and parameters: {'n_estimators': 250, 'max_depth': 4, 'learning_rate': 0.12980719972966576, 'subsample': 0.877172989023379, 'colsample_bytree': 0.5085907114378886, 'gamma': 0.015338569692314142}. Best is trial 95 with value: 0.28131809579227507.\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<optuna.study.study.Study at 0x79b88b7db310>"},"metadata":{}},{"name":"stdout","text":"Best trial: {'n_estimators': 250, 'max_depth': 4, 'learning_rate': 0.14463868242527206, 'subsample': 0.9029714947424823, 'colsample_bytree': 0.5305435748830561, 'gamma': 0.015968888840893466}\nBest clogloss: 0.28131809579227507\n","output_type":"stream"}]},{"cell_type":"code","source":"print('Best trial:', study.best_trial.params)\nprint('Best balanced_log_loss:', study.best_trial.value)","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:24.147826Z","iopub.execute_input":"2023-08-07T10:29:24.148861Z","iopub.status.idle":"2023-08-07T10:29:24.155838Z","shell.execute_reply.started":"2023-08-07T10:29:24.148823Z","shell.execute_reply":"2023-08-07T10:29:24.154598Z"},"trusted":true},"execution_count":18,"outputs":[{"name":"stdout","text":"Best trial: {'n_estimators': 250, 'max_depth': 4, 'learning_rate': 0.14463868242527206, 'subsample': 0.9029714947424823, 'colsample_bytree': 0.5305435748830561, 'gamma': 0.015968888840893466}\nBest balanced_log_loss: 0.28131809579227507\n","output_type":"stream"}]},{"cell_type":"code","source":"from sklearn.model_selection import train_test_split\n\nx_train, x_test, y_train, y_test = train_test_split(X,y,test_size=0.15)","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:24.157838Z","iopub.execute_input":"2023-08-07T10:29:24.158679Z","iopub.status.idle":"2023-08-07T10:29:24.171366Z","shell.execute_reply.started":"2023-08-07T10:29:24.158619Z","shell.execute_reply":"2023-08-07T10:29:24.169611Z"},"trusted":true},"execution_count":19,"outputs":[]},{"cell_type":"code","source":"import xgboost as xgb\ndtrain = xgb.DMatrix(x_train, label=y_train)\ndtest = xgb.DMatrix(x_test, label=y_test)","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:24.173002Z","iopub.execute_input":"2023-08-07T10:29:24.174918Z","iopub.status.idle":"2023-08-07T10:29:24.192414Z","shell.execute_reply.started":"2023-08-07T10:29:24.174867Z","shell.execute_reply":"2023-08-07T10:29:24.191388Z"},"trusted":true},"execution_count":20,"outputs":[]},{"cell_type":"code","source":"params ={'n_estimators': 300, 'max_depth': 7, 'learning_rate': 0.11083666084808587, 'subsample': 0.6646998689138404, 'colsample_bytree': 0.9993276251354577, 'gamma': 0.09161209891211826}","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:24.193943Z","iopub.execute_input":"2023-08-07T10:29:24.194295Z","iopub.status.idle":"2023-08-07T10:29:24.200632Z","shell.execute_reply.started":"2023-08-07T10:29:24.194264Z","shell.execute_reply":"2023-08-07T10:29:24.199504Z"},"trusted":true},"execution_count":21,"outputs":[]},{"cell_type":"code","source":"model = xgb.train(params, dtrain,300)","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:24.202724Z","iopub.execute_input":"2023-08-07T10:29:24.203138Z","iopub.status.idle":"2023-08-07T10:29:25.123729Z","shell.execute_reply.started":"2023-08-07T10:29:24.203106Z","shell.execute_reply":"2023-08-07T10:29:25.122740Z"},"trusted":true},"execution_count":22,"outputs":[{"name":"stdout","text":"[10:29:24] WARNING: ../src/learner.cc:767: \nParameters: { \"n_estimators\" } are not used.\n\n","output_type":"stream"}]},{"cell_type":"code","source":"y_pred = model.predict(dtest)","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:25.128499Z","iopub.execute_input":"2023-08-07T10:29:25.131244Z","iopub.status.idle":"2023-08-07T10:29:25.139935Z","shell.execute_reply.started":"2023-08-07T10:29:25.131200Z","shell.execute_reply":"2023-08-07T10:29:25.138919Z"},"trusted":true},"execution_count":23,"outputs":[]},{"cell_type":"code","source":"y_pred","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:25.145267Z","iopub.execute_input":"2023-08-07T10:29:25.148055Z","iopub.status.idle":"2023-08-07T10:29:25.159267Z","shell.execute_reply.started":"2023-08-07T10:29:25.148015Z","shell.execute_reply":"2023-08-07T10:29:25.157907Z"},"trusted":true},"execution_count":24,"outputs":[{"execution_count":24,"output_type":"execute_result","data":{"text/plain":"array([ 4.01794970e-01, -3.18232663e-02,  6.11064136e-01,  8.89729321e-01,\n        1.16453074e-01,  1.47869051e-01, -2.91372035e-02,  9.40503553e-02,\n       -3.98443900e-02,  1.02560678e-02, -1.76302101e-02,  8.25492859e-01,\n        8.52008443e-03,  2.51703203e-01,  4.40344632e-01,  3.81335855e-01,\n        3.28621775e-01,  3.20440121e-02,  6.84981495e-02,  2.37309739e-01,\n        7.33438432e-02,  1.22590043e-01, -1.39526092e-03,  1.11664444e-01,\n       -2.99167540e-02,  7.38781273e-01,  5.47379971e-01,  2.95557693e-04,\n        9.68140513e-02,  6.94513083e-01, -6.37892168e-03, -1.16434274e-02,\n        2.99214602e-01,  1.97723329e-01,  5.61706431e-04,  2.97197439e-02,\n       -2.67266389e-02,  4.30120751e-02,  1.03174222e+00, -3.35714892e-02,\n        4.43718396e-02,  7.35686600e-01, -8.84786472e-02, -8.98632631e-02,\n        3.61103922e-01,  1.45201668e-01,  4.89801317e-01,  1.62455328e-02,\n        8.11784327e-01, -1.42795043e-02, -7.58324144e-03,  8.08672607e-02,\n        1.04686081e-01,  1.59751669e-01,  1.87338777e-02,  6.30618818e-03,\n        2.51561612e-01,  5.55014789e-01, -3.11660990e-02, -1.90054793e-02,\n        7.96460867e-01,  1.37680814e-01,  2.13602334e-02, -1.41078485e-02,\n        4.65480298e-01, -1.83537155e-02, -2.17224192e-03,  6.04891896e-01],\n      dtype=float32)"},"metadata":{}}]},{"cell_type":"code","source":"from sklearn.metrics import accuracy_score\n\n# Convert probabilities to binary predictions\n\n\ny_pred_binary = [1 if p >= 0.5 else 0 for p in y_pred]\n\naccuracy = accuracy_score(y_test, y_pred_binary)\nprint(\"Accuracy: %.2f%%\" % (accuracy * 100.0))","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:25.160521Z","iopub.execute_input":"2023-08-07T10:29:25.160855Z","iopub.status.idle":"2023-08-07T10:29:25.180141Z","shell.execute_reply.started":"2023-08-07T10:29:25.160827Z","shell.execute_reply":"2023-08-07T10:29:25.173447Z"},"trusted":true},"execution_count":25,"outputs":[{"name":"stdout","text":"Accuracy: 94.12%\n","output_type":"stream"}]},{"cell_type":"code","source":"from sklearn.metrics import roc_auc_score\n\nauc_score = roc_auc_score(y_test, y_pred)","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:25.181993Z","iopub.execute_input":"2023-08-07T10:29:25.182747Z","iopub.status.idle":"2023-08-07T10:29:25.195768Z","shell.execute_reply.started":"2023-08-07T10:29:25.182713Z","shell.execute_reply":"2023-08-07T10:29:25.194399Z"},"trusted":true},"execution_count":26,"outputs":[]},{"cell_type":"code","source":"auc_score","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:25.197147Z","iopub.execute_input":"2023-08-07T10:29:25.197480Z","iopub.status.idle":"2023-08-07T10:29:25.205672Z","shell.execute_reply.started":"2023-08-07T10:29:25.197450Z","shell.execute_reply":"2023-08-07T10:29:25.204506Z"},"trusted":true},"execution_count":27,"outputs":[{"execution_count":27,"output_type":"execute_result","data":{"text/plain":"0.9841269841269841"},"metadata":{}}]},{"cell_type":"code","source":"from sklearn.metrics import confusion_matrix\n\nconfusion = confusion_matrix(y_test, y_pred_binary)\n\n# Extract true negatives (TN), false positives (FP), false negatives (FN), and true positives (TP) from the confusion matrix\nTN, FP, FN, TP = confusion.ravel()\n\n# Calculate the false positive rate (FPR) and false negative rate (FNR)\nFPR = FP / (FP + TN)\nFNR = FN / (FN + TP)\n\n# Print the false positive rate and false negative rate\nprint(\"False Positive Rate (FPR):\", FPR)\nprint(\"False Negative Rate (FNR):\", FNR)","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:25.211461Z","iopub.execute_input":"2023-08-07T10:29:25.211918Z","iopub.status.idle":"2023-08-07T10:29:25.223496Z","shell.execute_reply.started":"2023-08-07T10:29:25.211872Z","shell.execute_reply":"2023-08-07T10:29:25.222493Z"},"trusted":true},"execution_count":28,"outputs":[{"name":"stdout","text":"False Positive Rate (FPR): 0.018518518518518517\nFalse Negative Rate (FNR): 0.21428571428571427\n","output_type":"stream"}]},{"cell_type":"code","source":"competition_log_loss(y_test,y_pred)","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:25.224880Z","iopub.execute_input":"2023-08-07T10:29:25.225192Z","iopub.status.idle":"2023-08-07T10:29:25.245812Z","shell.execute_reply.started":"2023-08-07T10:29:25.225165Z","shell.execute_reply":"2023-08-07T10:29:25.244686Z"},"trusted":true},"execution_count":29,"outputs":[{"name":"stderr","text":"/tmp/ipykernel_32/4042287564.py:11: RuntimeWarning: divide by zero encountered in log\n  log_loss_0 = -np.sum((1 - y_true) * np.log(p_0))\n","output_type":"stream"},{"execution_count":29,"output_type":"execute_result","data":{"text/plain":"0.2809749143480316"},"metadata":{}}]},{"cell_type":"code","source":"lb=np.zeros(val.shape[0])","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:25.247320Z","iopub.execute_input":"2023-08-07T10:29:25.247822Z","iopub.status.idle":"2023-08-07T10:29:25.257094Z","shell.execute_reply.started":"2023-08-07T10:29:25.247780Z","shell.execute_reply":"2023-08-07T10:29:25.255875Z"},"trusted":true},"execution_count":30,"outputs":[]},{"cell_type":"code","source":"dval = xgb.DMatrix(val, label=lb)\n","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:25.258320Z","iopub.execute_input":"2023-08-07T10:29:25.258680Z","iopub.status.idle":"2023-08-07T10:29:25.276650Z","shell.execute_reply.started":"2023-08-07T10:29:25.258621Z","shell.execute_reply":"2023-08-07T10:29:25.275571Z"},"trusted":true},"execution_count":31,"outputs":[]},{"cell_type":"code","source":"pred=model.predict(dval)","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:25.277788Z","iopub.execute_input":"2023-08-07T10:29:25.278898Z","iopub.status.idle":"2023-08-07T10:29:25.288588Z","shell.execute_reply.started":"2023-08-07T10:29:25.278862Z","shell.execute_reply":"2023-08-07T10:29:25.287718Z"},"trusted":true},"execution_count":32,"outputs":[]},{"cell_type":"code","source":"pred","metadata":{"execution":{"iopub.status.busy":"2023-08-07T10:29:25.293341Z","iopub.execute_input":"2023-08-07T10:29:25.295760Z","iopub.status.idle":"2023-08-07T10:29:25.306706Z","shell.execute_reply.started":"2023-08-07T10:29:25.295717Z","shell.execute_reply":"2023-08-07T10:29:25.305796Z"},"trusted":true},"execution_count":33,"outputs":[{"execution_count":33,"output_type":"execute_result","data":{"text/plain":"array([0.4241249, 0.4241249, 0.4241249, 0.4241249, 0.4241249],\n      dtype=float32)"},"metadata":{}}]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}