1. A learning method of a neural network having a plurality of learning samples, said learning method identifying to which one of N categories each learning sample belongs using a data set consisting of N categories and comprising the steps of: obtaining in advance similarity for a learning sample for each learning sample in said data set; and performing learning by back propagation using said obtained similarity as a target signal of the neural network.