A biobjective model to select features with good classification quality and low cost

In this paper we address a multigroup classification problem in which we want to take into account, together with the generalization ability, costs associated with the features. This cost is not limited to an economical payment, but can also refer to risk, computational effort, space requirements, etc. In order to get a good generalization ability, we use support vector machines (SVM) as the basic mechanism by considering the maximization of the margin. We formulate the problem as a biobjective mixed integer problem, for which Pareto optimal solutions can be obtained.