A comparison study of credit scoring models

被引：0
|
作者：
Zhang, Defu [1 ,2 ]
Huang, Hongyi [1 ]
Chen, Qingshan [1 ]
Jiang, Yi [1 ]
机构：
[1] Xiamen Univ, Dept Comp Sci, Xiamen 361005, Peoples R China
[2] Longtop Grp Post doctoral Res Ctr, Xiamen 361005, Peoples R China
来源：
ICNC 2007: THIRD INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 1, PROCEEDINGS | 2007年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we consider a credit scoring problem. We compare three powerful credit scoring models: genetic programming (GP), backpropagation neural networks (BP) and support vector machines (SVM) when applied to this problem, then we give a combined model. The results show that the combined model produces good classification results.
引用
收藏
页码：15 / +
页数：2
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