The parameters = P(w t, ci ; 0) of the mixture component ci can be estimated as the fraction of training documents in cj that contain w 1 : 1 6tvtle; P(wt Icj; 0) = Bit P(ci di ) The multinomial event model assumes that a document di of length di is generated by a sequence of I d7 word events, where the outcome of each event is a word from the vocabulary V. Following McCallum and Nigam (1998), we assume that the document length distribution P(Id, I) does not depend on the class.
a document di can be represented as a vector of length I V , where each dimension t of the vector, denoted as Nit > 0, is the number of times word w t occurs in di.