Hi Ali.
As far as I know, MulitnomialNB just implements Mulitnomial Naive Bayes.
The paper just gives context, the docs don't say we implement that method.
I'm not sure how established their tricks actually are.
Best,
Andy
On 03/25/2015 09:53 AM, ali hürriyetoglu wrote:
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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