%0 Journal Article 
%A Labbé, Martine
%A Martínez Merino, Luisa Isabel
%A Rodríguez Chía, Antonio Manuel
%T Mixed integer linear programming for feature selection in support vector machine
%D 2019
%@ 0166-218X
%U http://hdl.handle.net/10498/31357
%X 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.
%K Mathematical programming
%K Kernel search algorithm
%K Supervised classification
%K Support vector machine
%K Feature selection
%~ Universidad de Cádiz