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| 最小总风险准则的贝叶斯网络个人信用评估模型* | |
| 引用本文： | 李旭升,郭春香,陈凯亚b.最小总风险准则的贝叶斯网络个人信用评估模型*[J].计算机应用研究,2009,26(1):50-53. |
| 作者姓名： | 李旭升 郭春香 陈凯亚b |
| 作者单位： | 1. 西南交通大学,经济管理学院,成都,610031 2. 四川大学,工商管理学院,成都,610065 3. 西南交通大学,电磁场与微波技术研究所,成都,610031 |
| 基金项目： | 国家自然科学基金资助项目(70371026)；四川省教育厅科研项目(2006C082) |
| 摘 要： | 将最小总风险准则MOR与贝叶斯网络分类器相结合，提出了一种新型信用评估模型。在两个真实数据集上以MOR用10层交叉验证对贝叶斯网络信用评估模型进行了测试，并与最小错误概率准则MPE的贝叶斯网络分类器的结果进行了对比。结果表明，基于MOR的贝叶斯网络分类模型可以有效地减小信用评估风险。 |
| 关 键 词： | 个人信用评估 最小总风险准则 最小错误概率准则 贝叶斯网络分类器 |
Bayesian network consumer credit scoring models based on minimum overall risk rule |
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| LI Xu-sheng,GUO Chun-xiang,CHEN Kai-yab.Bayesian network consumer credit scoring models based on minimum overall risk rule[J].Application Research of Computers,2009,26(1):50-53. | |
| Authors: | LI Xu-sheng GUO Chun-xiang CHEN Kai-yab |
| Affiliation: | (1.a.School of Economics & Management, b.Electromagnetics Institute, Southwest Jiaotong University, Chengdu 610031, China; 2. School of Business & Managerment, Sichuan University, Chengdu 610065, China) |
| Abstract: | This paper integrated MOR(minimum overall risk rule) into Bayesian network classifiers, and proposed new credit scoring models. According to MOR, they were tested using 10-fold cross validation with two real world data sets, and compared with Bayesian network classifier based on MPE. Results demonstrate that the Bayesian network classifiers based on MOR are able to reduce effectively the credit scoring risk. |
| Keywords: | consumer credit scoring minimum overall risk rule(MOR) minimum probability of error rule(MPE) Bayesian network classifiers |
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