comparision-tree-based-methods.py 文件源码

def xgbr(X,y):
    X_train,X_validation,y_train,y_validation = train_test_split(X,y,random_state=0)
    xgbr_boost = xgb.XGBRegressor(seed=1)
    xgbr_boost.fit(X_train,y_train.ravel())
    print 'training error:',1.0 - xgbr_boost.score(X_train,y_train)
    print 'validation error:',1.0 - xgbr_boost.score(X_validation,y_validation)
    time_fit(xgbr_boost,X_train,y_train.ravel())