Python QuantileExtremeValuesTransformer.fit_transform Examples

Example #1

def test_quantile_extremevalues_transformer():
    from sagemaker_sklearn_extension.preprocessing import QuantileExtremeValuesTransformer

    st_helper = SklearnTestHelper()

    data = np.array([
        [0.0, 0.0, 0.0],
        [-1.0, 1.0, 1.0],
        [-2.0, 2.0, 2.0],
        [-3.0, 3.0, 3.0],
        [-4.0, 4.0, 4.0],
        [-5.0, 5.0, 5.0],
        [-6.0, 6.0, 6.0],
        [-7.0, 7.0, 7.0],
        [-8.0, 8.0, 8.0],
        [-9.0, 9.0, 9.0],
        [-10.0, 10.0, 10.0],
        [-1e5, 1e6, 11.0],
    ])

    qt = QuantileExtremeValuesTransformer(threshold_std=2.0)
    qt.fit_transform(data)

    dshape = (relay.Any(), len(data[0]))
    _test_model_impl(st_helper, qt, dshape, data.astype("float32"))

Example #2

def test_extreme_value_transformer(X, X_expected):
    transformer = QuantileExtremeValuesTransformer(threshold_std=2.0)
    X_observed = transformer.fit_transform(X)

    assert_array_almost_equal(X_observed, X_expected)