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

E. Carrizosa, B. Martin-Barragan, D.R. Morales

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this paper we address a multi-group classification problem in which we want to take into account, together with the generalization ability, cots 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.
Original languageEnglish
Title of host publicationProceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004
Pages339-342
Number of pages4
DOIs
Publication statusPublished - 1 Jan 2004

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