Mixed Integer Linear Programming for Feature Selection in Support Vector Machine

Autor:	Labbé, Martine, Martínez-Merino, Luisa I., Rodríguez-Chía, Antonio M.
Rok vydání:	2018
Předmět:	Mathematics - Optimization and Control Computer Science - Machine Learning Statistics - Machine Learning 90C11
Druh dokumentu:	Working Paper
Popis:	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 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1808.02435 Zobrazit plný text záznamu View this record from Arxiv