test_BRKNN.py 文件源码

def test_BRKnna_no_labels_take_closest(self):
        data = csr.csr_matrix([[0, 1], [1, 1], [1, 1.1], [0, 1]])
        train_ids = [['lid0', 'lid1'], ['lid2', 'lid3'], ['lid2', 'lid3'], ['lid0', 'lid5']]
        mlb = MultiLabelBinarizer(sparse_output=True)
        y = mlb.fit_transform(train_ids)
        knn = BRKNeighborsClassifier(n_neighbors=2, threshold=0.6, mode='a')
        knn.fit(data, y)

        pred = knn.predict(csr.csr_matrix([[0, 1]])).todense()
        print(pred)
        np.testing.assert_array_equal([[1, 0, 0, 0, 0]], pred)