def test_predict_proba_weighting():
query = np.array([-1, 1])
pool_classifiers = create_pool_classifiers()
des_test = DES(pool_classifiers, mode='weighting')
competences = np.array([0.5, 1.0, 0.2])
des_test.estimate_competence = MagicMock(return_value=competences)
des_test.n_classes = 2
expected = np.array([0.5769, 0.4231])
predicted_proba = des_test.predict_proba_instance(query)
assert np.isclose(predicted_proba, expected, atol=0.01).all()
def test_predict_proba_selection():
query = np.array([-1, 1])
pool_classifiers = create_pool_classifiers() + create_pool_classifiers()
des_test = DES(pool_classifiers, mode='selection')
selected_indices = [0, 1, 5]
des_test.select = MagicMock(return_value=selected_indices)
des_test.n_classes = 2
expected = np.array([0.61, 0.39])
predicted_proba = des_test.predict_proba_instance(query)
assert np.isclose(predicted_proba, expected, atol=0.01).all()
def test_predict_proba_hybrid():
query = np.array([-1, 1])
pool_classifiers = create_pool_classifiers() + create_pool_classifiers()
des_test = DES(pool_classifiers, mode='hybrid')
des_test.n_classes = 2
selected_indices = [0, 1, 5]
competences = np.array([0.55, 1.0, 0.2, 0.60, 0.75, 0.3])
expected = np.array([0.5744, 0.4256])
des_test.estimate_competence = MagicMock(return_value=competences)
des_test.select = MagicMock(return_value=selected_indices)
predicted_proba = des_test.predict_proba_instance(query)
assert np.isclose(predicted_proba, expected, atol=0.01).all()
