Study on parameters selection of LSSVR based on grid-diamond search method

Determining the kernel function and regularization parameters for support vector machine (SVM) is very problem-dependent in practice. A popular method to deciding the kernel parameters is cross validation method. But this makes the training process time-consuming. In this paper we propose using grid-diamond search method to choose the kernel parameters. Experiment results show that the grid-diamond search method can choose proper parameters of LSSVR and GDS is the fastest algorithm among the selecting parameter while providing better simulation result.