Linear Programming v-Nonparallel Support Vector Machine

In this paper, base on the nonparallel hyper plane classifier, v-Nonparallel Support Vector Machine (v-NPSVM), we proposed its linear programming formulation, termed as v - LPNPSVM. v-NPSVM which has been proved superior to the twin support vector machines (TWSVMs), is parameterized by the quantity v to let ones effectively control the number of Support Vectors. Compared with the quadratic programming problem of v-NPSVM, the 1-norm regularization term is introduced to v-LPNPSVM to make them to be linear programming problem which can be solved fast and easily. We also introduce kernel functions directly into the formulation for the nonlinear case. The numerical experiments on lots of data sets verify that our v-LPNPSVM is superior to TWSVMs and faster than standard NPSVMs.