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


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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.

作者简介

V. Svetlov

Skobeltsyn Institute of Nuclear Physics; Physical Department

编辑信件的主要联系方式.
Email: svetlov.vsevolod@gmail.com
俄罗斯联邦, Moscow; Moscow

S. Dolenko

Skobeltsyn Institute of Nuclear Physics

Email: svetlov.vsevolod@gmail.com
俄罗斯联邦, Moscow

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