test_model_selection_sklearn.py 文件源码

def test_classes__property():
    # Test that classes_ property matches best_estimator_.classes_
    X = np.arange(100).reshape(10, 10)
    y = np.array([0] * 5 + [1] * 5)
    Cs = [.1, 1, 10]

    grid_search = dcv.GridSearchCV(LinearSVC(random_state=0), {'C': Cs})
    grid_search.fit(X, y)
    assert_array_equal(grid_search.best_estimator_.classes_,
                       grid_search.classes_)

    # Test that regressors do not have a classes_ attribute
    grid_search = dcv.GridSearchCV(Ridge(), {'alpha': [1.0, 2.0]})
    grid_search.fit(X, y)
    assert not hasattr(grid_search, 'classes_')

    # Test that the grid searcher has no classes_ attribute before it's fit
    grid_search = dcv.GridSearchCV(LinearSVC(random_state=0), {'C': Cs})
    assert not hasattr(grid_search, 'classes_')

    # Test that the grid searcher has no classes_ attribute without a refit
    grid_search = dcv.GridSearchCV(LinearSVC(random_state=0),
                                   {'C': Cs}, refit=False)
    grid_search.fit(X, y)
    assert not hasattr(grid_search, 'classes_')