%0 Journal Article
%T Incremental learning algorithm based on SVM<br>基于支持向量机的增量学习算法*
%A CAO Jie
%A LIU Zhi-jing
%A <br>曹杰
%A 刘志镜
%J 计算机应用研究
%D 2007
%I 
%X By analyzing the characteristics of support vectors and the processing of incremental learning, this paper presented a new algorithm of incremental learning. It discarded useless samples and kept the testing accuracy, meanwhile reduced the training time. Numerical and applicable results illustrate that the technique is feasible and effective in the end.
%K structural risk minimization
%K support vector
%K incremental learning<br>结构风险最小化
%K 支持向量
%K 增量学习
%K 支持向量机
%K 增量学习算法
%K based
%K learning
%K algorithm
%K 应用
%K 数值实验
%K 训练时间
%K 测试精度
%K 样本
%K 分类
%K 学习过程
%K 性质
%K 分析
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=C793235A4E87B8F64E1C6A855E54A062&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=5D311CA918CA9A03&sid=B6DA1AC076E37400&eid=2A3781E88AB1776F&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=7