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Mixed integer linear programming for feature selection in support vector machine

par Labbé, Martine ;Martínez-Merino, Luisa L.I.;Rodríguez-Chía, Antonio A.M.
Référence Discrete applied mathematics, 261, page (276-304)
Publication Publié, 2019-05-01

Article révisé par les pairs

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Résumé :

This work focuses on support vector machine (SVM)with feature selection. A MILP formulation is proposed for the problem. The choice of suitable features to construct the separating hyperplanes has been modeled in this formulation by including a budget constraint that sets in advance a limit on the number of features to be used in the classification process. We propose both an exact and a heuristic procedure to solve this formulation in an efficient way. Finally, the validation of the model is done by checking it with some well-known data sets and comparing it with classical classification methods.