[Python] sklearn ColumnTransformer with MultilabelBinarizer

I wonder if it is possible to use a MultilabelBinarizer within a ColumnTransformer.

I have a toy pandas dataframe like:

df = pd.DataFrame({"id":[1,2,3],
"text": ["some text", "some other text", "yet another text"],
"label": [["white", "cat"], ["black", "cat"], ["brown", "dog"]]})

preprocess = ColumnTransformer(
[
('vectorizer', CountVectorizer(), 'text'),
('binarizer', MultiLabelBinarizer(), ['label']),

],
remainder='drop')


this code, however, throws an exception:

~/lib/python3.7/site-packages/sklearn/pipeline.py in _fit_transform_one(transformer, X, y, weight, message_clsname, message, **fit_params)
714 with _print_elapsed_time(message_clsname, message):
715 if hasattr(transformer, 'fit_transform'):
--> 716 res = transformer.fit_transform(X, y, **fit_params)
717 else:
718 res = transformer.fit(X, y, **fit_params).transform(X)

TypeError: fit_transform() takes 2 positional arguments but 3 were given


With OneHotEncoder the ColumnTransformer does work.

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