Bayesian Classification: Naive bayes Although the naive bayes assumption is incorrect in the context of text processing, it often does quite well, partly because the decisions made can be optimal even in the face of the inaccurate assumption a Decision rule for Naive bayes: Decide sif s=argmax k[log P(5k+smiinc log p(oi lsel P(Oils and p(e are computed via Maximum-Likelihoo Estimation, perhaps with appropriate smoothing, from a labeled training corpus P(|)=C(y)C( P()=C()/C(n) 20212/5 Natural Language Processing--Word Sense Disambiguation 102021/2/5 Natural Language Processing -- Word Sense Disambiguation 10 Bayesian Classification: Naïve Bayes ◼ Although the Naïve Bayes assumption is incorrect in the context of text processing, it often does quite well, partly because the decisions made can be optimal even in the face of the inaccurate assumption. ◼ Decision rule for Naïve Bayes: Decide s ’ if s ’ =argmaxsk[log P(sk )+Σvj in c log P(vj|sk )] ◼ P(vj|sk ) and P(sk ) are computed via Maximum-Likelihood Estimation, perhaps with appropriate smoothing, from a labeled training corpus. ◼ P(vj|sk ) = C(vj ,sk )/C(sk ) ◼ P(sk ) = C(sk )/C(w)