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
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GB
regressor = make_pipeline(SimpleImputer(), LinearRegression())
cross_val_score(regressor, X, y)Д
y
ZB
y
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GB
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DB