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.