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