This is due to the Laplace smoothening. If I understand correctly, you want the classification to fail if there is a new feature value (e.g., a word that is not in the vocabulary when you are doing text classification)?
You can set the alpha parameter to 0 (see http://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.MultinomialNB.html#sklearn.naive_bayes.MultinomialNB) which would disable the Laplace smoothening. Best, Sebastian Raschka > On Sep 3, 2014, at 6:20 AM, Karimkhan Pathan <[email protected]> wrote: > > I have trained my classifier using 20 domain datasets using MultinomialNB. > And it is working fine for these 20 domains. > > Issue is, if I make query which contains text which does not belongs to any > of these 20 domain, even it gives classification result. > > Is it possible that if query does not belongs to any of 20 domain, it should > get probability value 0? > ------------------------------------------------------------------------------ > Slashdot TV. > Video for Nerds. Stuff that matters. > http://tv.slashdot.org/ > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general ------------------------------------------------------------------------------ Slashdot TV. Video for Nerds. Stuff that matters. http://tv.slashdot.org/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
