[scikit-learn] Naive Bayes - Multinomial Naive Bayes tf-idf

[Marcin Mirończuk]

Hi,
In our experiments, we use a Multinomial Naive Bayes (MNB). The traditional
MNB implies the TF weight of the words. We read in documentation
http://scikit-learn.org/stable/modules/naive_bayes.html which describes
Multinomial Naive Bayes that "... where the data are typically represented
as word vector counts, although tf-idf vectors are also known to work well
in practice". The "word vector counts" is a TF and it is well known. We
have a problem which the "tf-idf vectors". In this case, i.e. tf-idf  it
was implemented the approach of the D. M. Rennie et all Tackling the Poor
Assumptions of Naive Bayes Text Classification? In the documentation, there
are not any citation of this solution.

Best,

-- 
Marcin M.
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