Abstract:

Firstly, some critical issues about the nonlinear binaryclass support vector machine (SVM) are studied. Secondly, the function of the nonlinear mapping used in nonlinear classification, the connotation of the dimension disaster, and the essence of the kernel function are elaborated. Thirdly, a new method to obtain connotative nonlinear mapping of the kernel function is put forward and the expression for the binaryclass SVM is presented. And finally, dataclassification experiments with the binaryclass SVMs are performed.

Key words: support vector machine, nonlinear mapping, dimension disaster, kernel function