Naive Bayesian Method-Maximum posteriori probability

Then go on to write the last article.

When the naive Bayes method is classified, a posteriori probability distribution P (y=ck|) is computed for a given input x by learning the model. X=X), then output the class with the largest posteriori probability as the class of X. The posterior probability calculation is based on Bayesian theorem:

P (y=ck| x=x) =p (x=x| Y=ck ) *p (y=ck)/(sum (k) P (x=x| Y=CK) *p (y=ck))

Final Jiancheng: Y=arg max (CK) p (y=ck) multiplicative P (X (J) =x (j) | Y=CK).

Naive Bayesian Method-Maximum posteriori probability