Evolving ensemble of classifiers in random subspace

Authors:
Albert Hung-Ren Ko;Robert Sabourin;Alceu de Souza Britto, Jr.
Affiliations:
University of Quebec, Montreal, QC, Canada;University of Quebec, Montreal, QC, Canada;Pontifical Catholic University of Parana, Curitiba, Brazil
Venue:
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Year:
2006

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Abstract

Various methods for ensemble selection and classifier combination have been designed to optimize the results of ensembles of classifiers. Genetic algorithm (GA) which uses the diversity for the ensemble selection could be very time consuming. We propose compound diversity functions as objective functions for a faster and more effective GA searching. Classifiers selected by GA are combined by a proposed pairwise confusion matrix transformation, which offer strong performance boost for EoCs.