MOGE: GP classification problem decomposition using multi-objective optimization

A novel approach to classification is proposed in which a Paretobased 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 multiobjective 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. Categories and Subject Descriptors I.2.2 [Artificial Intelligence]: Automatic Programming

• Type: Conference
• Year: 2006
• Where: GECCO
• Authors: Andrew R. McIntyre, Malcolm I. Heywood
• Keywords: Classification Problems, Cluster Consistency Problem, Formulation Enables Classification, GECCO 2006, Optimization