Using fuzzy, neural and fuzzy-neural combination methods in ensembles with different levels of diversity

Authors:
Anne M. P. Canuto;Marjory C. C. Abreu
Affiliations:
Informatics and Applied Mathematics Department, Federal University of RN Natal, RN, Brazil;Informatics and Applied Mathematics Department, Federal University of RN Natal, RN, Brazil
Venue:
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Year:
2007

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Abstract

Classifier Combination has been investigated as an alternative to obtain improvements in design and/or accuracy for difficult pattern recognition problems. In the literature, many combination methods and algorithms have been developed, including methods based on computational Intelligence, such as: fuzzy sets, neural networks and fuzzy neural networks. This paper presents an evaluation of how different levels of diversity reached by the choice of the components can affect the accuracy of some combination methods. The aim of this analysis is to investigate whether or not fuzzy, neural and fuzzy-neural combination methods are affected by the choice of the ensemble members.