A minimum seeking approach for support vector machine

被引：0
|
作者：
Peng, PY [1 ]
Zhang, YP [1 ]
机构：
[1] United Technol Res Ctr, E Hartford, CT 06108 USA
来源：
Soft Computing with Industrial Applications, Vol 17 | 2004年 / 17卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A fast optimization approach is proposed in this paper to identify the "support vectors" of a given set of points. The computational issue of the classic quadratic programming technique is eliminated by the proposed "minimum seeking" approach. Minimum seeking approach that is developed front the geometric concept is used to update (add or delete) the candidate support vector set. The proposed minimum seeking approach has the benefits of "unsupervised" learning and faster convergent rate.. The simulation results using elevator faulty signals validate the usefulness of this approach.
引用
收藏
页码：143 / 148
页数：6
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