摘要
首先,对非线性二分类支持向量机方法中的几个关键问题进行了研究;其次,阐明了非线性映射在解决非线性分类问题时所起的作用,揭示了维数灾难的具体内涵,理清了核函数方法的本质;第三,提出了求取核函数中隐含非线性映射的方法,获取了非线性二分类支持向量机的表达式;第四,利用二分类支持向量机完成了一系列数据分类实验。
Firstly, some critical issues about the nonlinear binary class support vector machine （SVM） are studied. Sec ondly, 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 ker nel function is put forward and the expression for the binar^class SVM is presented. And finally, data-classification experi- ments with the binary-class SVMs are performed.
出处
《计算机工程与科学》
CSCD
北大核心
2010年第5期41-44,共4页
Computer Engineering & Science
基金
国家自然科学基金资助项目(60804041)
关键词
支持向量机
非线性映射
维数灾难
核函数
support vector machine
nonlinear mapping
dimension disaster
kernel function
