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+1 vote
in Machine Learning by (4.2k points)

I'm using sklearn.pipeline.Pipeline to chain feature extractors and a classifier. Is there a way to combine multiple feature selection classes (for example the ones from sklearn.feature_selection.text) in parallel and join their output?

My code right now looks as follows:

pipeline = Pipeline([
    ('vect', CountVectorizer()),
    ('tfidf', TfidfTransformer()),
    ('clf', SGDClassifier())])

It results in the following:

vect -> tfidf -> clf

I want to be able to specify a pipeline that looks as follows:

vect1 -> tfidf1 \
                 -> clf
vect2 -> tfidf2 /

1 Answer

+2 votes
by (6.8k points)

This has been implemented recently in the master branch of sci-kit-learn under the name FeatureUnion:

For more details on this, check out the  Scikit Tutorial With Python.

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