Credit risk evaluation with least square support vector machine
文献类型：期刊论文
| 作者 | Lai, Kin Keung; Yu, Lean; Zhou, Ligang; Wang, Shouyang
|
| 刊名 | ROUGH SETS AND KNOWLEDGE TECHNOLOGY, PROCEEDINGS
 |
| 出版日期 | 2006 |
| 卷号 | 4062页码:490-495 |
| 关键词 | credit risk evaluation least square support vector machine |
| ISSN号 | 0302-9743 |
| 英文摘要 | 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. |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000239623500071 |
| 出版者 | SPRINGER-VERLAG BERLIN |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/3539]  |
| 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. |
入库方式： OAI收割
来源：数学与系统科学研究院
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