def test_IH_is_used(example_estimate_competence, create_pool_classifiers): X, y, neighbors, distances, dsel_processed, _ = example_estimate_competence expected = [0, 0, 1] query = np.ones((3, 2)) ds_test = BaseDS(create_pool_classifiers, with_IH=True, IH_rate=0.5) ds_test.fit(X, y) ds_test.DSEL_processed_ = dsel_processed ds_test.get_competence_region = MagicMock(return_value=(distances, neighbors)) predicted = ds_test.predict(query) assert np.array_equal(predicted, expected)
def test_predict_proba_instance_called(index, example_estimate_competence, create_pool_classifiers): X, y, neighbors, distances, _, _ = example_estimate_competence query = np.atleast_2d([1, 1]) ds_test = BaseDS(create_pool_classifiers, with_IH=True, IH_rate=0.10) ds_test.fit(X, y) neighbors = neighbors[index, :] distances = distances[index, :] ds_test.get_competence_region = MagicMock(return_value=(distances, neighbors)) ds_test.predict_proba_with_ds = MagicMock( return_value=np.atleast_2d([0.25, 0.75])) proba = ds_test.predict_proba(query) assert np.allclose(proba, np.atleast_2d([0.25, 0.75]))
def test_predict_proba_IH_knn(index, example_estimate_competence, create_pool_classifiers): X, y, neighbors, distances, _, dsel_scores = example_estimate_competence query = np.atleast_2d([1, 1]) ds_test = BaseDS(create_pool_classifiers, with_IH=True, IH_rate=0.5) ds_test.fit(X, y) ds_test.DSEL_scores = dsel_scores neighbors = neighbors[index, :] distances = distances[index, :] ds_test.get_competence_region = MagicMock(return_value=(distances, neighbors)) ds_test.roc_algorithm_.predict_proba = MagicMock( return_value=np.atleast_2d([0.45, 0.55])) proba = ds_test.predict_proba(query) assert np.array_equal(proba, np.atleast_2d([0.45, 0.55]))