BaggingClassifier的超参数 n_estimators=N,max_features=n能够用GridSearchCV搜索吗

来源：13-4 oob (Out-of-Bag) 和关于Bagging的更多讨论

qq_慕姐45445

2021-06-26

from sklearn.ensemble import BaggingClassifier
from sklearn.model_selection import GridSearchCV
bagging_clf = BaggingClassifier(DecisionTreeClassifier()
bootstrap=True, oob_score=True,bootstrap_features=True)
param_grid_bagging = {‘n_estimatorsl’:[100,200,500,1000],
’,max_samples’:[10,20,50,100,200,500,1000],
‘max_features’:[5,10,20,30,40]}

bagging_clf=GridSearchCV(bagging_clf,param_grid_bagging,scoring={‘AUC’:‘roc_auc’},refit=‘AUC’,cv=10)

bagging_clf.fit(x_train1,y_train)
print(bagging_clf.best_estimator_)

我试了一下不行。啊，在那些地方要修改？谢谢老师

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