Dear List members,
I saw a Note on [1] about MultinomialNB. The note is:
"For the rationale behind the names coef_ and intercept_, i.e. naive Bayes
as a linear classifier, see J. Rennie et al. (2003), Tackling the poor
assumptions of naive Bayes text classifiers, ICML."
Does it mean the implementation of the MultinomialNB apply steps that are
mentioned in Rennie et al? If not, is there an easy way, via parameters, to
let it apply those steps? My feature extraction code is as follows:
vectorizer2 = TfidfVectorizer(use_idf=True, vocabulary=myvocab,
ngram_range=(1,2), sublinear_tf=True)
X2_train = vectorizer2.fit_transform(label_tweetDF.text.values)
Thanks for your time.
Ali
[1]
http://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.MultinomialNB.html
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