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 modelled 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.Comment: 37 pages, 20 figure