def test_classify(index, expected): query = np.atleast_2d([1, 1]) knora_u_test = KNORAU(create_pool_classifiers()) knora_u_test.fit(X_dsel_ex1, y_dsel_ex1) knora_u_test.DFP_mask = np.ones(knora_u_test.n_classifiers) knora_u_test.neighbors = neighbors_ex1[index, :] knora_u_test.distances = distances_ex1[index, :] prediction = knora_u_test.classify_instance(query) assert prediction == expected
def test_classify(index, expected): query = np.atleast_2d([1, 1]) knora_u_test = KNORAU(create_pool_classifiers()) knora_u_test.fit(X_dsel_ex1, y_dsel_ex1) knora_u_test.DFP_mask = np.ones(knora_u_test.n_classifiers) knora_u_test.neighbors = neighbors_ex1[index, :] knora_u_test.distances = distances_ex1[index, :] predictions = [] for clf in knora_u_test.pool_classifiers: predictions.append(clf.predict(query)[0]) prediction = knora_u_test.classify_instance(query, np.array(predictions)) assert prediction == expected