A Fast Lagrangian Support Vector Machine Model

被引：0
|
作者：
Yuan, Jian [1 ]
Chen, YongQi [1 ]
Yang, XiangSheng [1 ]
机构：
[1] Ningbo Univ, Sch Sci & Technol, Ningbo 315211, Zhejiang, Peoples R China
来源：
ADVANCES IN COMPUTER SCIENCE, INTELLIGENT SYSTEM AND ENVIRONMENT, VOL 3 | 2011年 / 106卷
关键词：
Laerangian support vector machine; online learning; classification;
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：
Lagrangian support vector machine(LSVM) is a kind of method with good generalization ability. But, LSVM is not suitable for classification online because the computation complexity. So in this paper, a fast LSVM is proposed. This method can deduce running time because it fully utilizes the historical training results and reduces memory and calculates time. Finally, an example is accomplished to demonstrate the effect of fast LSVM.
引用
收藏
页码：65 / 69
页数：5
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