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This work focuses on support vector machine (SVM) with feature selection. AMILP formulation is proposed for the problem. The choice of suitable featuresto construct the separating hyperplanes has been modelled in this formulationby including a budget constraint that sets in advance a limit on the number offeatures to be used in the classification process. We propose both an exact anda 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 datasets and comparing it with classical classification methods.

Mixed Integer Linear Programming for Feature Selection in Support Vector Machine