test_split.py 文件源码

def test_nested_cv():
    # Test if nested cross validation works with different combinations of cv
    rng = np.random.RandomState(0)

    X, y = make_classification(n_samples=15, n_classes=2, random_state=0)
    labels = rng.randint(0, 5, 15)

    cvs = [LeaveOneLabelOut(), LeaveOneOut(), LabelKFold(), StratifiedKFold(),
           StratifiedShuffleSplit(n_iter=3, random_state=0)]

    for inner_cv, outer_cv in combinations_with_replacement(cvs, 2):
        gs = GridSearchCV(Ridge(), param_grid={'alpha': [1, .1]},
                          cv=inner_cv)
        cross_val_score(gs, X=X, y=y, labels=labels, cv=outer_cv,
                        fit_params={'labels': labels})