Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/103850
Type: Artigo de periódico
Title: Statistical Evaluation Of Pruning Methods Applied In Hidden Neurons Of The Mlp Neural Network [avaliação Estatística De Métodos De Poda Aplicados Em Neurônios Intermediários Da Rede Neural Mlp]
Author: Silvestre M.R.
Ling L.L.
Abstract: There are several papers on pruning methods in the artificial neural networks area. However, with rare exceptions, none of them presents an appropriate statistical evaluation of such methods. In this article, we proved statistically the ability of some methods to reduce the number of neurons of the hidden layer of a multilayer perceptron neural network (MLP), and to maintain the same landing of classification error of the initial net. They are evaluated seven pruning methods. The experimental investigation was accomplished on five groups of generated data and in two groups of real data. Three variables were accompanied in the study: apparent classification error rate in the test group (REA); number of hidden neurons, obtained after the application of the pruning method; and number of training/retraining epochs, to evaluate the computational effort. The non-parametric Friedman's test was used to do the statistical analysis.
Editor: 
Rights: fechado
Identifier DOI: 10.1109/TLA.2006.4472121
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-77958181102&partnerID=40&md5=21ced0193cfb49e33971cd84b0a627c0
Date Issue: 2006
Appears in Collections:Unicamp - Artigos e Outros Documentos

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