sklearn_estimators.py 文件源码

def __init__(self,name,kwargs):
        import xgboost as xgb
        kwargs = kwargs.copy()
        if "random_state" in kwargs:
            kwargs["seed"] = kwargs["random_state"]
            kwargs.pop("random_state")
        super(GCXGBClassifier,self).__init__(name,xgb.XGBClassifier,kwargs)