Credit risk evaluation with least square support vector machine

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	Credit risk evaluation with least square support vector machine
	Lai, Kin Keung ; Yu, Lean ; Zhou, Ligang ; Wang, Shouyang
	2006
发表期刊	ROUGH SETS AND KNOWLEDGE TECHNOLOGY, PROCEEDINGS
ISSN	0302-9743
卷号	4062 页码:490-495
摘要	Credit risk evaluation has been the major focus of financial and banking industry due to recent financial crises and regulatory concern of Basel II. Recent studies have revealed that emerging artificial intelligent techniques are advantageous to statistical models for credit risk evaluation. In this study, we discuss the use of least square support vector machine (LSSVM) technique to design a credit risk evaluation system to discriminate good creditors from bad ones. Relative to the Vapnik's support vector machine, the LSSVM can transform a quadratic programming problem into a linear programming problem thus reducing the computational complexity. For illustration, a published credit dataset for consumer credit is used to validate the effectiveness of the LSSVM.
关键词	credit risk evaluation least square support vector machine
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000239623500071
出版者	SPRINGER-VERLAG BERLIN
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/3540
专题	系统科学研究所
通讯作者	Lai, Kin Keung
作者单位	1.Hunan Univ, Coll Business Adm, Changsha 410082, Peoples R China 2.City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R China 3.Chinese Acad Sci, Inst Syst Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Lai, Kin Keung,Yu, Lean,Zhou, Ligang,et al. Credit risk evaluation with least square support vector machine[J]. ROUGH SETS AND KNOWLEDGE TECHNOLOGY, PROCEEDINGS,2006,4062:490-495.
APA	Lai, Kin Keung,Yu, Lean,Zhou, Ligang,&Wang, Shouyang.(2006).Credit risk evaluation with least square support vector machine.ROUGH SETS AND KNOWLEDGE TECHNOLOGY, PROCEEDINGS,4062,490-495.
MLA	Lai, Kin Keung,et al."Credit risk evaluation with least square support vector machine".ROUGH SETS AND KNOWLEDGE TECHNOLOGY, PROCEEDINGS 4062(2006):490-495.