The multinomial logistic classifier uses a generalization of the sigmoid, called the softmax function, to compute the probability p(y = c|x). The softmax function softmax takes a vector z = [z 1 , z 2 , ..., z k ] of k arbitrary values and maps them to a probability distribution, with each value in the range (0,1), and all the values summing to 1. Like the sigmoid, it is an exponential function.