如何使用sklearn管道元素的输出

我有三个特点:

feature_one -> number of tokens in the given sentence.  
feature_two -> number of verbs in the given sentence.  
feature_three -> number of tokens - number of verbs in the given sentence.  
(feature_one - feature_two)

我写了自定义变压器 feature_one 和 feature_two feature_three 这样我就可以使用 功能1 功能二 通过以下方式运行管道:

Pipeline([
        #input to feature_one and feature_two is list of sentences.
        ("feature", FeatureUnion([
            ("feature_one", feature_one_transformer()),
            ("feature_two", feature_two_transformer())          
        ])),

        ("feature_three", feature_three_transformer())    
])

feature\u one\u变压器:

class feature_one_transformer(BaseEstimator, TransformerMixin):

    def __init__(self):
        pass

    def fit(self, x, y):
        return self

    def transform(self, sentence_list):
        number_of_tokens_in_sentence_list = list()

        for sentence in sentence_list:
            number_of_tokens = compute_number_of_tokens

            number_of_tokens_in_sentence_lista.append(number_of_tokens)

        return pandas.DataFrame(number_of_tokens_in_sentence_list)

class feature_two_transformer(BaseEstimator, TransformerMixin):
    def __init__(self):
        pass

    def fit(self, x, y):
        return self

    def transform(self, sentence_list):
        number_of_verbs_in_sentence_list = list()

        for sentence in sentence_list:
            number_of_verbs = compute_number_of_verbs_in_sentence

            number_of_verbs_in_sentence_lista.append(number_of_verbs)

        return pandas.DataFrame(number_of_verbs_in_sentence_list)

有人能告诉我应该如何为feature\u三编写自定义transformer,以及如何在管道中使用,以便使用feature\u一和feature\u二个transformer的结果吗。非常感谢。