基于sklearn接口的分类
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.metrics import accuracy_score...importances: [0.002148238569679191, 0.0046703830672789074, 0.33366676380518245, 0.6595146145578594]
进行超参数搜索...X_train, X_test, y_train, y_test = train_test_split(data, target, test_size=0.2, random_state=1)
estimator...'learning_rate': [0.05, 0.1,],
'n_estimators': [2000, 3000],
'max_depth': [2, 3, ],
'min_samples_split...': [2, 3],
}
gbm = GridSearchCV(estimator, param_grid)
gbm.fit(X_train, y_train)
print('Best parameters