Article
Mixed integer linear programming for feature selection in support vector machine
Author/s | Labbé, Martine
Martínez Merino, Luisa Isabel Rodríguez Chía, Antonio Manuel |
Department | Universidad de Sevilla. Departamento de Estadística e Investigación Operativa |
Publication Date | 2019 |
Deposit Date | 2022-10-24 |
Published in |
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Abstract | This work focuses on support vector machine (SVM) with feature selection. A MILP formula-
tion is proposed for the problem. The choice of suitable features to construct the separating
hyperplanes has been modeled in this ... This work focuses on support vector machine (SVM) with feature selection. A MILP formula- tion 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. |
Citation | Labbé, M., Martínez Merino, L.I. y Rodríguez Chía, A.M. (2019). Mixed integer linear programming for feature selection in support vector machine. Discrete Applied Mathematics, 261, 276-304. https://doi.org/10.1016/j.dam.2018.10.025. |
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