Lars Buitinck <larsmans@...> writes:
> The way to combine HV and
> Tfidf is
>
> hashing = HashingVectorizer(non_negative=True, norm=None)
> tfidf = TfidfTransformer()
> hashing_tfidf = Pipeline([("hashing", hashing), ("tidf", tfidf)])
>
I notice your use of the non_negative option in HashingVectorizer(), when
following hashing with TF-IDF.
Since using non_negative eliminates some information, I am curious whether
there is any harm to allowing negative values as inputs to the TF-IDF
function. In the general case, feature values whether positive or negative
should simply scale up based on how document-infrequent they are, so I don't
see the harm of allowing negative values.
-Apu
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