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Credit risk evaluation using a weighted least squares SVM classifier with design of experiment for parameter selection

文献类型：期刊论文

作者Yu, Lean1,2; Yao, Xiao1; Wang, Shouyang1; Lai, K. K.3
刊名EXPERT SYSTEMS WITH APPLICATIONS
出版日期2011-11-01
卷号38期号:12页码:15392-15399
关键词Credit risk evaluation Weighted LSSVM classifier Least squares algorithm Design of experiment Parameter selection
ISSN号0957-4174
DOI10.1016/j.eswa.2011.06.023
英文摘要Support vector machines (SVM) is proved to be one of the most effective tool in credit risk evaluation. However, the performance of SVM is sensitive not only to the algorithm for solving the quadratic programming but also to the parameters setting in its learning machines as well as to the importance of different classes. In order to solve these issues, this paper proposes a weighted least squares support vector machine (LSSVM) classifier with design of experiment (DOE) for parameter selection for credit risk evaluation. In this approach, least squares algorithm is used to solve the quadratic programming, the DOE is used for parameter selection in SVM modelling and weights in LSSVM are used to emphasize the importance of difference classes. For illustration purpose, two publicly available credit datasets are selected to demonstrate the effectiveness and feasibility of the proposed weighted LSSVM classifier. The results show that the proposed weighted LSSVM classifier with DOE can produce the promising classification results in credit risk evaluation, relative to other classifiers listed in this study. (C) 2011 Elsevier Ltd. All rights reserved.
资助项目National Science Fund for Distinguished Young Scholars (NSFC)[71025005] ; National Natural Science Foundation of China (NSFC)[90924024] ; Chinese Academy of Sciences ; Hangzhou Key Laboratory of E-Business and Information Security, Hangzhou Normal University ; K.C. Wong Education Foundation, Hong Kong
WOS研究方向Computer Science ; Engineering ; Operations Research & Management Science
语种英语
WOS记录号WOS:000295193400110
出版者PERGAMON-ELSEVIER SCIENCE LTD
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/11716]  
专题系统科学研究所
通讯作者Yu, Lean
作者单位1.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, MADIS, Beijing 100190, Peoples R China
2.Hangzhou Normal Univ, Hangzhou Key Lab E Business & Informat Secur, Hangzhou 310036, Zhejiang, Peoples R China
3.City Univ Hong Kong, Dept Management Sci, Kowloon, Hong Kong, Peoples R China
推荐引用方式
GB/T 7714		 Yu, Lean,Yao, Xiao,Wang, Shouyang,et al. Credit risk evaluation using a weighted least squares SVM classifier with design of experiment for parameter selection[J]. EXPERT SYSTEMS WITH APPLICATIONS,2011,38(12):15392-15399.
APA Yu, Lean,Yao, Xiao,Wang, Shouyang,&Lai, K. K..(2011).Credit risk evaluation using a weighted least squares SVM classifier with design of experiment for parameter selection.EXPERT SYSTEMS WITH APPLICATIONS,38(12),15392-15399.
MLA Yu, Lean,et al."Credit risk evaluation using a weighted least squares SVM classifier with design of experiment for parameter selection".EXPERT SYSTEMS WITH APPLICATIONS 38.12(2011):15392-15399.

入库方式： OAI收割

来源：数学与系统科学研究院

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