%0 Journal Article
%T Influence to Nonlinear Classification Support Vector Machines by Separable Variables Kernel Function<br>变元可分离核函数对非线性支持向量分类机的影响
%A YUAN Feng-Shan
%A ZHU Si-Ming
%A <br>原峰山
%A 朱思铭
%J 计算机科学
%D 2007
%I 
%X It is proved that under Hilbert space separable variables function can satisfy condition of Mercer theorem as kernel function to provide a new method in selecting new kernel function of nonlinear calssification machines based on support vector machine. Compared with other nonlinear classification support vector machines structured by known kernel function, the kernel function selected by new method can give better result.
%K Separable variables function
%K Kernel function
%K Classification algorithm<br>变元可分离函数
%K 核函数
%K 分类算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=2C190DC57C33B1A7CA4D761987F8547D&yid=A732AF04DDA03BB3&vid=339D79302DF62549&iid=E158A972A605785F&sid=D5C9DC4EF2F78008&eid=31611641D4BB139F&journal_id=1002-137X&journal_name=计算机科学&referenced_num=2&reference_num=5