text_plain_output_1.png
from lightgbm import LGBMClassifier

from sklearn.model_selection import cross_val_score, train_test_split, GridSearchCV

lgr = LGBMClassifier()
param_dist = {'learning_rate': [0.1], 'num_leaves': [100], 'n_estimators': [300], 'device': ['gpu']}
LGBM_model = GridSearchCV(lgr, param_grid=param_dist, cv=3, scoring='f1', verbose=5)
LGBM_model.fit(features_train, target_train)
LGBM_model.best_estimator_