An improved Hyper-sphere support vector machine

被引：0
|
作者：
Liu, Shuang [1 ]
Liu, Yongkui [1 ]
Wang, Bo [1 ]
Feng, Xiwei [2 ]
机构：
[1] Dalian Natl Univ, Coll Comp Sci & Engn, Dalian 116600, Peoples R China
[2] Liaoning Shihua Univ, Sch Comp & Commun Engn, Liaoning 113001, Peoples R China
来源：
ICNC 2007: THIRD INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 1, PROCEEDINGS | 2007年
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：
Hyper-sphere support vector machines are proposed for solving multi-class classification problem. How to correctly class's the intersections of hyper-spheres is important foil sphere structure support vector machines. Based on the analysis of such data samples, this paper presents a new simple classification rule which leads to a better generalization accuracy than the existing sub-hyper-sphere SVMs. Experimental results show our method is feasible and improves the performance of the resulting minimum bounding sphere-based classifier.
引用
收藏
页码：497 / +
页数：2
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