[MRG] MAINT Adds tag categorical to OneHotEncoder (#14068)

scikit-learn · Jun 24, 2019 · 0bdd920 · 0bdd920
1 parent f41cd1e
commit 0bdd920
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Showing 2 changed files with 8 additions and 3 deletions.
diff --git a/sklearn/preprocessing/_encoders.py b/sklearn/preprocessing/_encoders.py
@@ -144,6 +144,9 @@ def _transform(self, X, handle_unknown='error'):
 
         return X_int, X_mask
 
+    def _more_tags(self):
+        return {'X_types': ['categorical']}
+
 
 class OneHotEncoder(_BaseEncoder):
     """Encode categorical integer features as a one-hot numeric array.
@@ -656,6 +659,3 @@ def inverse_transform(self, X):
             X_tr[:, i] = self.categories_[i][labels]
 
         return X_tr
-
-    def _more_tags(self):
-        return {'X_types': ['categorical']}
diff --git a/sklearn/preprocessing/tests/test_encoders.py b/sklearn/preprocessing/tests/test_encoders.py
@@ -671,3 +671,8 @@ def test_categories(density, drop):
             assert cat_list[drop_idx] == drop_cat
     assert isinstance(ohe_test.drop_idx_, np.ndarray)
     assert ohe_test.drop_idx_.dtype == np.int_
+
+
+@pytest.mark.parametrize('Encoder', [OneHotEncoder, OrdinalEncoder])
+def test_encoders_has_categorical_tags(Encoder):
+    assert 'categorical' in Encoder()._get_tags()['X_types']