Neural network credit-risk evaluation model based on back-propagation algorithm

被引：0
|
作者：
Li, RZ [1 ]
Pang, SL [1 ]
Xu, JM [1 ]
机构：
[1] S China Univ Technol, Coll Traff & Commun, Guangzhou 510640, Peoples R China
来源：
2002 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-4, PROCEEDINGS | 2002年
关键词：
back-propagation algorithm; credit-risk evaluation model; neural network; linear discriminant analysis;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The research establishes a neural network credit-risk evaluation model by using back-propagation algorithm. The model is evaluated by the credits for 120 applicants. The 120 data are separated in three groups: a "good credit" group, a "middle credit" group and a "bad credit" group. The simulation shows that the neural network credit-risk evaluation model has higher classification accuracy compared with the traditional parameter statistical approach, that is linear discriminant analysis. We still give a learning algorithm and a corresponding algorithm of the model.
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页码：1702 / 1706
页数：5
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