Enhancing decision-based neural networks through local competition

In this paper, the decision-based neural network (DBNN) learning algorithm is modified to stimulate local competition. Performance is assessed in ten UCI databases, resulting in improved results at the expense of a relatively low increase of the computational burden.

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Bibliographic Details
Published in:Neurocomputing (Amsterdam) 2006-03, Vol.69 (7), p.905-908
Main Authors: Camps-Valls, Gustavo, Gómez-Chova, Luis, Vila-Francés, Joan, Martín-Guerrero, José D., Serrano-López, Antonio J., Soria-Olivas, Emilio
Format: Article
Language:English
Subjects:
Competitive credit-assignment scheme
Decision-based neural network
Hierarchical network structure
Local competition
UCI database
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Description
Summary:In this paper, the decision-based neural network (DBNN) learning algorithm is modified to stimulate local competition. Performance is assessed in ten UCI databases, resulting in improved results at the expense of a relatively low increase of the computational burden.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2005.09.006