Research on Combination Kernel Function of Support Vector Machine

Abstract

The kernel function and parameters selection is a key problem in the research of support vector machine. After discussing the influence of support vector machine on kernel parameters and error penalty factors, a new kernel function CombKer was proposed and constructed. The CombKer kernel function is a kind of combination kernel function, which combines the Gaussian RBF kernel function that has the local characteristic, with the linear kernel function that has the global characteristic. Finally, some experiments on different domains data in the support vector machine constructed by the CombKer kernel function were done, and the results showed the better ability on prediction of this kind of support vector machine and proved the validation of the CombKer kernel function.