With a multinomial event model, samples (feature vectors) represent the frequencies with which certain events have been generated by a multinomial formula_36 where formula_37 is the probability that event occurs (or such multinomials in the multiclass case). A feature vector formula_38 is then a histogram, with formula_7 counting the number of times event was observed in a particular instance. This is the event model typically used for document classification, with events representing the occurrence of a word in a single document (see bag of words assumption). The likelihood of observing a histogram is given by