DocumentCode
3207742
Title
Constructive and pruning methods for neural network design
Author
Costa, Marcelo Azevedo ; Braga, Antonio Pádua ; De Menezes, Benjamin Rodrigues
Author_Institution
Univ. Fed. de Minas Gerais, Belo Horizonte, Brazil
fYear
2002
fDate
2002
Firstpage
49
Lastpage
54
Abstract
This paper presents methods to improve generalization of multilayer perceptron (MLP) by pruning the original topology without loss in performance. Topology information and validation sets are used. The results show that these techniques are able to choose a minimum network topology and to simplify trained networks.
Keywords
generalisation (artificial intelligence); multilayer perceptrons; MLP; constructive methods; generalization; minimum network topology; multilayer perceptron; neural network design; topology information sets; topology pruning; topology validation sets; trained networks; Multilayer perceptrons; Network topology; Neural networks; Performance loss; Sampling methods; Shape; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. SBRN 2002. Proceedings. VII Brazilian Symposium on
Print_ISBN
0-7695-1709-9
Type
conf
DOI
10.1109/SBRN.2002.1181434
Filename
1181434
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