def test_classify_instance_weighting(): query = np.atleast_2d([-1, 1]) pool_classifiers = create_pool_classifiers() + create_pool_classifiers() des_test = DES(pool_classifiers, mode='weighting') competences = np.array([0.55, 1.0, 0.2, 0.60, 0.75, 0.3]) des_test.estimate_competence = MagicMock(return_value=competences) predictions = [] for clf in des_test.pool_classifiers: predictions.append(clf.predict(query)[0]) predicted_label = des_test.classify_instance(query, np.array(predictions)) assert predicted_label == 1.0
def test_classify_instance_selection(): query = np.atleast_2d([-1, 1]) pool_classifiers = create_pool_classifiers() + create_pool_classifiers() des_test = DES(pool_classifiers, mode='selection') # competences = [0.55, 1.0, 0.2, 0.65, 0.75, 0.8] selected_index = [0, 1, 5] des_test.select = MagicMock(return_value=selected_index) predictions = [] for clf in des_test.pool_classifiers: predictions.append(clf.predict(query)[0]) predicted_label = des_test.classify_instance(query, np.array(predictions)) assert predicted_label == 0.0