核函数参数选择是支撑向量机(SVM)研究的主要问题之一。提出检验样本是否呈高斯分布的方法,确定最优核参数选择的依据,采用两组数据集分别进行回归实验,验证所提出方法的有效性。
The kernel parameter selection is one of the key problems for support vector machine(SVM). Presented a new way to select the kernel function and its parameter, it is based on the characteristics of data distribution. Presents an approach to determine Gauss distribution,and then on the basis of determining Gauss distribution, discusses how to select the kernel function and its parameter. The simulation ex-periments demonstrate the feasibility and the effectiveness of the presented approach.