关键词: 支持向量机, 核函数, 模型选择

Abstract: This paper  introduces  generalized  Laguerre  polynomial based on Laguerre orthogonal  polynomial, and  derives a new set of kernel function—Laguerre kernel function from generalized Laguerre  polynomial. The performance and robustness of the presented kernel are investigated on bi-spiral benchmark data set as well as five data sets from the UCI benchmark repository. The experiment results demonstrate that the presented kernel has better robustness and generalization performance compared with commonly used kernel functions（polynomial kernel and Radial Basis Function etc.）. Moreover, the Laguerre kernel has one parameter which only chooses from natural number, thus parameter optimization is facilitated greatly.

Key words: Support Vector Machine（SVM）, kenel function, model selection