Development of the algorithm of adaptive construction of hierarchical neural network classifiers

Abstract

This paper presents the development of the algorithm for adaptive construction of hierarchical neural network classifiers based on automatic modification of the desired response of a perceptron with a small number of neurons in a single hidden layer. Improved versions of the algorithm are tested on standard benchmark problems Vowels and MNIST. A discussion of the results, strengths and weaknesses of the algorithm, directions of further work on its testing and improvement, is provided.