集成模型（回归）用于训练Boston数据以预测其结果

from sklearn.datasets import load_boston
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.ensemble import RandomForestRegressor,ExtraTreesRegressor,GradientBoostingRegressor
from sklearn.metrics import mean_squared_error,mean_absolute_error
#导入数据集
boston = load_boston()
#查看数据详情print(boston.DESCR)
X = boston.data
y = boston.target
#对数据进行划分处理
X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.25,random_state=33)
ss_X = StandardScaler()
ss_y =StandardScaler()
#分别对训练集和测试集的特征及目标变量进行标准化操作
X_