我注意到cv_values_无论scoring选项如何，来自 RidgeCV 的值始终处于相同的指标中。下面是一个例子：
from sklearn.linear_model import RidgeCV
from sklearn.datasets import load_boston
boston = load_boston()
mod = RidgeCV(store_cv_values = True, scoring = 'r2')
fit = mod.fit(boston.data, boston.target)
print(fit)
print(fit.cv_values_)
mod = RidgeCV(store_cv_values = True, scoring = 'neg_mean_squared_error')
fit = mod.fit(boston.data, boston.target)
print(fit)
print(fit.cv_values_)
输出是：
RidgeCV(alphas=(0.1, 1.0, 10.0), cv=None, fit_intercept=True, gcv_mode=None,
normalize=False, scoring='r2', store_cv_values=True)
[[ 7.61705436 7.83092421 8.2298466 ]
[ 2.50029583 2.31181064 2.11665248]
[ 7.98280614 7.95286299 7.87166914]
...,
[ 5.24271689 5.50191347 5.84802692]
[ 3.7448827 4.01778493 4.40457956]
[ 0.0859419 …