test_model_selection.py 文件源码

def test_cache_cv():
    X, y = make_classification(n_samples=100, n_features=10, random_state=0)
    X2 = X.view(CountTakes)
    gs = dcv.GridSearchCV(MockClassifier(), {'foo_param': [0, 1, 2]},
                          cv=3, cache_cv=False, scheduler='sync')
    gs.fit(X2, y)
    assert X2.count == 2 * 3 * 3  # (1 train + 1 test) * n_params * n_splits

    X2 = X.view(CountTakes)
    assert X2.count == 0
    gs.cache_cv = True
    gs.fit(X2, y)
    assert X2.count == 2 * 3  # (1 test + 1 train) * n_splits