Development of the algorithm of adaptive construction of hierarchical neural network classifiers
- 作者: Svetlov V.A.1,2, Dolenko S.A.1
-
隶属关系:
- Skobeltsyn Institute of Nuclear Physics
- Physical Department
- 期: 卷 26, 编号 1 (2017)
- 页面: 40-46
- 栏目: Article
- URL: https://journals.rcsi.science/1060-992X/article/view/194948
- DOI: https://doi.org/10.3103/S1060992X17010076
- ID: 194948
如何引用文章
详细
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
补充文件
