Using weighted combination-based methods in ensembles with different levels of diversity

Authors:
Thiago Dutra;Anne M. P. Canuto;Marcilio C. P. de Souto
Affiliations:
Informatics and Applied Mathematics Department, Federal University of Rio Grande do Norte(UFRN), Natal, RN, Brazil;Informatics and Applied Mathematics Department, Federal University of Rio Grande do Norte(UFRN), Natal, RN, Brazil;Informatics and Applied Mathematics Department, Federal University of Rio Grande do Norte(UFRN), Natal, RN, Brazil
Venue:
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Year:
2006

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Abstract

There are two main approaches to combine the output of classifiers within a multi-classifier system, which are: combination-based and selection-based methods. This paper presents an investigation of how the use of weights in some non-trainable simple combination-based methods applied to ensembles with different levels of diversity. It is aimed to analyse whether the use of weights can decrease the dependency of ensembles on the diversity of their members.