K
n_fold = 5
kfold =
KFold(n_splits = n_fold, random_state=0, shuffle = True)
for fold_n, (train_index, valid_index) in enumerate(kfold.split(X,y)):
Size: a a a
K
n_fold = 5
kfold =
KFold(n_splits = n_fold, random_state=0, shuffle = True)
for fold_n, (train_index, valid_index) in enumerate(kfold.split(X,y)):
K
y
regressor = make_pipeline(SimpleImputer(), LinearRegression())
cross_val_score(regressor, X, y)
GB
y
Д
ZB
ZB
GB
regressor = make_pipeline(SimpleImputer(), LinearRegression())
cross_val_score(regressor, X, y)
Д
y
ZB
y
AG
GB
GZ
Ю
SD
SD
DB