Séminaire Modélisation, Optimisation, Dynamique

DC programming and DCA for Gaussian Kernel Support Vector Machines with Feature Selection

par Dr Vinh Thanh Ho

Europe/Paris
XR203 (XLIM)

XR203

XLIM

FST-Université de Limoges 123 Av. Albert Thomas, 87000 Limoges
Description

We consider the support vector machines problem with the feature selection using Gaussian kernel function. This problem takes the form of a nonconvex minimization problem with binary variables. We investigate an exact penalty technique to deal with the binary variables. The resulting optimization problem can be expressed as a DC (Difference of Convex functions) program on which DCA (DC Algorithm) is applied. Numerical experiments on several benchmark real datasets show the efficiency of the proposed algorithm in terms of both feature selection and classification when compared with the existing algorithm.