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Mixed integer linear programming for feature selection in support vector machine. (English) Zbl 1420.90038

Summary: 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. 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.

MSC:

90C11 Mixed integer programming

Software:

UCI-ml
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References:

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