An improved fuzzy support vector machine for credit rating

被引：0
|
作者：
Hao, Yanyou [1 ,2 ]
Chi, Zhongxian [1 ]
Yan, Deqin [3 ]
Yue, Xun [1 ]
机构：
[1] Dalian Univ Technol, Dept Comp Sci & Engn, Dalian 116024, Peoples R China
[2] Liaoning Natl Univ, Dept Comp Sci, Dalian 116029, Peoples R China
[3] Dalian Branch CCB, Dalian 116001, Peoples R China
来源：
NETWORK AND PARALLEL COMPUTING, PROCEEDINGS | 2007年 / 4672卷
关键词：
fuzzy support vector machine (FSVM); fuzzy membership; vague sets; credit rating;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
In order to classify data with noises or outliers, Fuzzy support vector machine (FSVM) improve the generalization power of traditional SVM by assigning a fuzzy membership to each input data point. In this paper, an improved FSVM based on vague sets is proposed by assigning a truth-membership and a false-membership to each data point. And we reformulate the improved FSVM so that different input points can make different contributions to decision hyperplane. The effectiveness of the improved FSVM is verified in credit rating; the experiment results show that our method is promising.
引用
收藏
页码：495 / +
页数：3
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