Python sklearn_type_of_targetの例

コード例 #1

    def testTypeOfTarget(self):
        raws = [
            np.array([[0, 1], [0, 0]]),  # multilabel
            np.random.randint(2, size=(5, 3, 3)),  # ndim > 2, unknown
            np.array([[]]),  # ndim == 2, shape[1] == 0, unknown
            np.array([[1, 2], [1, 2]]),
            np.array([1, 2, 3]),
            np.array([.1, .2, 3]),
            np.array([[.1, .2, 3]]),
            np.array([[1., .2]]),
            np.array([[1., 2., 3]]),
            np.array([[1, 2]]),
            np.array([1, 2]),
            np.array([["a"], ["b"]], dtype=object),
            [[1, 2]],
            [],  # empty list
        ]

        for raw in raws:
            self.assertEqual(type_of_target(raw).execute(),
                             sklearn_type_of_target(raw))

        t = mt.tensor(raws[0], chunk_size=1)
        self.assertEqual(type_of_target(t).execute(),
                         sklearn_type_of_target(raws[0]))

        with self.assertRaises(ValueError):
            type_of_target('sth')

コード例 #2

ファイル: test_multiclass.py プロジェクト: haijohn/mars

def test_type_of_target(setup):
    raws = [
        np.array([[0, 1], [0, 0]]),  # multilabel
        np.random.randint(2, size=(5, 3, 3)),  # ndim > 2, unknown
        np.array([[]]),  # ndim == 2, shape[1] == 0, unknown
        np.array([[1, 2], [1, 2]]),
        np.array([1, 2, 3]),
        np.array([.1, .2, 3]),
        np.array([[.1, .2, 3]]),
        np.array([[1., .2]]),
        np.array([[1., 2., 3]]),
        np.array([[1, 2]]),
        np.array([1, 2]),
        np.array([["a"], ["b"]], dtype=object),
        [[1, 2]],
        [],  # empty list
    ]

    for raw in raws:
        assert type_of_target(raw).to_numpy() == sklearn_type_of_target(raw)

    t = mt.tensor(raws[0], chunk_size=1)
    assert type_of_target(t).to_numpy() == sklearn_type_of_target(raws[0])

    with pytest.raises(ValueError):
        type_of_target('sth')