test_BRKNN.py 文件源码

def test_BRKnnb_predict_dense(self):
        data = csr.csr_matrix([[0, 1], [1, 1], [1.5, 1], [0.5, 1]])
        train_ids = [['lid0', 'lid1'], ['lid0', 'lid1'], ['lid4', 'lid3'], ['lid4', 'lid5']]
        mlb = MultiLabelBinarizer(sparse_output=False)
        y = mlb.fit_transform(train_ids)

        knn = BRKNeighborsClassifier(mode='b', n_neighbors=3)
        knn.fit(data, y)

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