def test_select_none_competent(): des_p_test = DESP(create_pool_classifiers()) des_p_test.n_classes = 2 competences = np.ones(des_p_test.n_classifiers) * 0.49 indices = des_p_test.select(competences) expected = np.array([[True, True, True]]) assert np.array_equal(expected, indices)
def test_select_three_classes(index, expected): query = np.atleast_2d([1, 1]) des_p_test = DESP(create_pool_classifiers()) des_p_test.fit(X_dsel_ex1, y_dsel_ex1) des_p_test.n_classes = 3 des_p_test.neighbors = neighbors_ex1[index, :] des_p_test.distances = distances_ex1[index, :] competences = des_p_test.estimate_competence(query) selected = des_p_test.select(competences) assert np.array_equal(selected, expected)
def test_select_ten_classes(index, ): query = np.atleast_2d([1, 1]) des_p_test = DESP(create_pool_classifiers()) des_p_test.fit(X_dsel_ex1, y_dsel_ex1) des_p_test.n_classes = 10 des_p_test.DFP_mask = np.ones(des_p_test.n_classifiers) des_p_test.neighbors = neighbors_ex1[index, :] des_p_test.distances = distances_ex1[index, :] competences = des_p_test.estimate_competence(query) selected = des_p_test.select(competences) assert selected == list(range(des_p_test.n_classifiers))
def test_select_none_competent(): des_p_test = DESP(create_pool_classifiers()) des_p_test.n_classes = 2 competences = np.ones(des_p_test.n_classifiers) * 0.49 indices = des_p_test.select(competences) assert indices == list(range(des_p_test.n_classifiers))