Feature selection for support vector machines using Generalized Benders Decomposition

Haldun Aytug

European Journal of Operational Research, 2015, vol. 244, issue 1, 210-218

Abstract: We propose an exact method, based on Generalized Benders Decomposition, to select the best M features during induction. We provide details of the method and highlight some interesting parallels between the technique proposed here and some of those published in the literature. We also propose a relaxation of the problem where selecting too many features is penalized. The original method performs well on a variety of data sets. The relaxation, though competitive, is sensitive to the penalty parameter.

Keywords: Data mining; Feature selection; Support vector machines (SVM); Generalized Benders Decomposition (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:244:y:2015:i:1:p:210-218

DOI: 10.1016/j.ejor.2015.01.006

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