def METHOD_NAME(selection):
    df = vaex.datasets.iris()
    if selection is None:
        vaex_result = df.ml.metrics.mean_squared_error(df.petal_width, df.petal_length)
        sklearn_result = metrics.mean_squared_error(df.petal_width.values, df.petal_length.values)
        assert vaex_result == sklearn_result
    else:
        vaex_result = df.ml.metrics.mean_squared_error(df.petal_width, df.petal_length, selection=selection)
        for i, sel in enumerate(selection):
            sklearn_result = metrics.mean_squared_error(df.filter(sel).petal_width.values, df.filter(sel).petal_length.values)
            np.testing.assert_almost_equal(vaex_result[i], sklearn_result)