def test_classify_instance():
query = np.atleast_2d([1, -1])
des_knn_test = DESKNN(create_pool_classifiers() * 4, k=2)
des_knn_test.select = MagicMock(return_value=[0, 1, 2, 3, 5, 6, 7, 9])
predicted = des_knn_test.classify_instance(query)
assert predicted == 0
def test_classify_instance():
query = np.atleast_2d([1, -1])
des_knn_test = DESKNN(create_pool_classifiers() * 4, k=2)
des_knn_test.select = MagicMock(return_value=[0, 1, 2, 3, 5, 6, 7, 9])
predictions = []
for clf in des_knn_test.pool_classifiers:
predictions.append(clf.predict(query)[0])
predicted = des_knn_test.classify_instance(query, predictions=np.array(predictions))
assert predicted == 0
