def test_FeatureReducer(self):
df = self.test_df
target = 'gap expt'
fr = FeatureReducer()
# ultra-basic case: are we reducing at least 1 feature?
df = fr.fit_transform(df, target)
self.assertTrue(df.shape[1] < self.test_df.shape[1])
# ensure metadata is being written correctly
self.assertTrue(target not in fr.retained_features)
self.assertTrue(len(list(fr.removed_features.keys())) == 2)
# ensure other combinations of feature reducers are working
fr = FeatureReducer(reducers=('corr', 'rebate'), n_rebate_features=40)
df = fr.fit_transform(self.test_df, target)
self.assertEqual(df.shape[1], 41) # 40 features + target
self.assertTrue(target in df.columns)
# ensure the same thing works when fraction is used
fr = FeatureReducer(reducers=('rebate', ), n_rebate_features=0.2)
df = fr.fit_transform(self.test_df, target)
self.assertEqual(df.shape[1], 83 + 1)
# test transferability
df2 = self.test_df
df2 = fr.transform(df2, target)
self.assertListEqual(df.columns.tolist(), df2.columns.tolist())
def test_FeatureReducer_transferability(self):
# ensure the same thing works when fraction is used
fr = FeatureReducer(reducers=("rebate", ), n_rebate_features=0.2)
df = fr.fit_transform(self.test_df, self.target)
self.assertEqual(df.shape[1], 83 + 1)
# test transferability
df2 = deepcopy(self.test_df)
df2 = fr.transform(df2, self.target)
self.assertListEqual(df.columns.tolist(), df2.columns.tolist())