MOGE: GP classification problem decomposition using multi-objective optimization

Authors:
Andrew McIntyre;Malcolm Heywood
Affiliations:
Dalhousie University, Halifax, Nova Scotia, Canada;Dalhousie University, Halifax, Nova Scotia, Canada
Venue:
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Year:
2006

Citing 6
Cited 7

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Abstract

A novel approach to classification is proposed in which a Pareto-based ranking of individuals is used to encourage multiple individuals to participate in the solution. To do so, the classification problem is re-expressed as a cluster consistency problem, thus allowing utilization of techniques from multi-objective optimization. Such a formulation enables classification problems to be automatically decomposed and solved by several specialist classifiers rather than by a single 'super' individual. In this paper, we demonstrate the proposed approach to two benchmark binary problems and recommend a natural extension to multi-class problems. Results indicate the general appropriateness of the approach.