cross_val_score函数的参数scoring 求MSE

可以使用scoring='neg_mean_squared_error'来求MSE，因为neg_mean_squared_error返回的是负的MSE，所以需要将结果取反，即将返回的值乘以-1。使用如下代码：

from sklearn.model_selection import cross_val_score
from sklearn.linear_model import LinearRegression
from sklearn.datasets import load_boston

boston = load_boston()
X = boston.data
y = boston.target

lr = LinearRegression()
mse_scores = cross_val_score(lr, X, y, scoring='neg_mean_squared_error')
mse_scores = -mse_scores
print(mse_scores)

输出结果为：

[ 12.46171222  26.04898699  33.07413798  80.76237112  33.31360656]