Multi-core Twin Support Vector Machines Based on Binary PSO Optimization

Abstract

How to select the suitable parameters and kernel model is a very important problem for Twin Support vector Machines (TWSVM). In order to solve this problem, one solving algorithm called binary PSO for optimizing the parameters of multi-core Twin Support Vector Machines (BPSO-MTWSVM) is proposed in this paper. Firstly, introducing multiple kernel functions, the twin support vector machines based on multi-core is constructed. This strategy is a good way to solve the kernel model selection. However, it has added three adjustable parameters. In order to solve the parameters selection problem which contain TWSVM parameters and multi-core model parameters, binary PSO (BPSO) is introduced. BPSO is an optimization algorithm who has strong robustness and good global searching ability. Finally, compared with the classical TWSVM the experimental results show that BPSO-MTWSVM has higher classification accuracy.