def test_extract_metafeature_names_unsupervised_02(self, groups, summary): """Test .extract_metafeature_names method.""" X, _ = utils.load_xy(0) mfe = MFE(groups=groups, summary=summary) mtf_names_1 = mfe.fit(X.values).extract(suppress_warnings=True)[0] # Note: by default, .extract_metafeature_names should check wether # 'y' was fitted or not if .fit was called before. Therefore, here, # supervised=True is expected to be ignored and behave like # supervised=False. mtf_names_2 = mfe.extract_metafeature_names(supervised=True) mtf_names_3 = mfe.extract_metafeature_names(supervised=False) assert tuple(mtf_names_1) == mtf_names_2 == mtf_names_3
def test_extract_with_time_output_pandas_dataframe_unsupervised(self): X, _ = load_xy(2) extractor = MFE(measure_time="total", groups="general").fit(X.values) expected_mtfs = extractor.extract_metafeature_names() res = extractor.extract(out_type=pd.DataFrame) assert isinstance(res, pd.DataFrame) assert res.values.shape == (2, len(expected_mtfs)) and np.array_equal( res.columns, expected_mtfs)
def test_extract_output_pandas_dataframe(self): X, y = load_xy(2) extractor = MFE(groups="general").fit(X.values, y.values) expected_mtfs = extractor.extract_metafeature_names() res = extractor.extract(out_type=pd.DataFrame) assert isinstance(res, pd.DataFrame) assert res.values.shape == (1, len(expected_mtfs)) and np.array_equal( res.columns, expected_mtfs)
def test_extract_metafeature_names_unsupervised_01(self, groups, summary): """Test .extract_metafeature_names method.""" X, _ = utils.load_xy(0) mfe = MFE(groups=groups, summary=summary) mtf_names_1 = mfe.extract_metafeature_names(supervised=False) mtf_names_2 = mfe.fit(X.values).extract(suppress_warnings=True)[0] assert mtf_names_1 == tuple(mtf_names_2)