TST update make_column_transformer test + add comment (scikit-learn#12156)

jorisvandenbossche · jnothman · commit 4a6b5b8832ba · 2018-10-15T10:11:34.000+11:00
Follow-up on scikit-learn#12152 And added comment why transformer_weights is not passed through, see scikit-learn#11183 (review) for more discussion
diff --git a/sklearn/compose/_column_transformer.py b/sklearn/compose/_column_transformer.py
@@ -751,6 +751,8 @@ def make_column_transformer(*transformers, **kwargs):
                             ['categorical_column'])])
 
     """
+    # transformer_weights keyword is not passed through because the user
+    # would need to know the automatically generated names of the transformers
     n_jobs = kwargs.pop('n_jobs', None)
     remainder = kwargs.pop('remainder', 'drop')
     sparse_threshold = kwargs.pop('sparse_threshold', 0.3)
diff --git a/sklearn/compose/tests/test_column_transformer.py b/sklearn/compose/tests/test_column_transformer.py
@@ -499,12 +499,12 @@ def test_make_column_transformer_kwargs():
     norm = Normalizer()
     ct = make_column_transformer(('first', scaler), (['second'], norm),
                                  n_jobs=3, remainder='drop',
-                                 sparse_threshold=0.3)
+                                 sparse_threshold=0.5)
     assert_equal(ct.transformers, make_column_transformer(
         ('first', scaler), (['second'], norm)).transformers)
     assert_equal(ct.n_jobs, 3)
     assert_equal(ct.remainder, 'drop')
-    assert_equal(ct.sparse_threshold, 0.3)
+    assert_equal(ct.sparse_threshold, 0.5)
     # invalid keyword parameters should raise an error message
     assert_raise_message(
         TypeError,
