EVALUATION FUNCTIONS FOR THE EVOLUTIONARY DESIGN OF MULTICLASS SUPPORT VECTOR MACHINES
Ana Carolina Lorena, André C. P. L. F. de Carvalho · International Journal of Computational Intelligence and Applications · 2009
Support Vector Machines were originally proposed to solve two-class classification problems. When they are applied to multiclass classification problems, usually a decomposition approach is followed, in which the original multiclass problem is decomposed into multiple binary sub-problems, whose solutions are afterwards combined. There are several strategies to decompose the multiclass problem. Genetic Algorithms (GAs) can be used to optimize the decomposition according to the performance obtained in the overall multiclass problem solution. This paper presents a study on possible evaluation functions that can be used by the GA in order to evaluate a given decomposition.