A NEURAL NETWORK METHOD OF CLASSIFICATION FOR LARGE NUMBER OF CATALOGS

Neural network has been used for pattern recognition popularly. The training time of neural network for N catalogs classification increases exponentially with N, so it is difficult to deal with large number of catalogs by normal neural networks. Based on binary partition method and decision tree, a neural network array for classifying large number of catalogs is proposed in this paper. Each element in the array is a simple neural network which only processes 2 catalog classification. Thus the architecture of network array is flexible and expansible, and the training time is reduced largely. It is proved that the mean error of classifying N catalogs with neural network array is smaller than that with a normal neural network. Experiment shows that this method can classify large number of catalogs well.