@misc{10498/31357,
year = {2019},
url = {http://hdl.handle.net/10498/31357},
abstract = {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. Wepropose 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.},
publisher = {Elsevier},
keywords = {Mathematical programming},
keywords = {Kernel search algorithm},
keywords = {Supervised classification},
keywords = {Support vector machine},
keywords = {Feature selection},
title = {Mixed integer linear programming for feature selection in support vector machine},
doi = {10.1016/j.dam.2018.10.025},
author = {Labbé, Martine and Martínez Merino, Luisa Isabel and Rodríguez Chía, Antonio Manuel},
}