a document 1 d (an outcome of random variable D) and a set of classes C =
c 1, . . . , c N (outcomes of the random variable C), we can use Bayes’ Rule to compute
P(c 1|d), . . . , P(c N|d), which computes the likelihood of observing class
label c i given that document d was observed. Document d can then be labeled
with the class with the highest probability of being observed given the document.
That is, Naïve Bayes classifies a document d as follows