Consumer credit scoring using an artificial immune system algorithm

被引：8

作者：

Leung, Kevin ^{[1
]}

Cheong, France ^{[1
]}

Cheong, Christopher ^{[1
]}

机构：

[1] RMIT Univ, Sch Business IT, Melbourne, Vic, Australia

来源：

2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS | 2007年

关键词：

D O I：

10.1109/CEC.2007.4424908

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Credit scoring has become a very important task in the credit industry and its use has increased at a phenomenal speed through the mass issue of credit cards since the 1960s. This paper compares the performance of current classifiers against an artificial intelligence technique based on the natural immune system, named simple artificial immune system (SAIS). Experiments were performed on three benchmark credit datasets and SAIS was found to be a very competitive classifier.

引用

页码：3377 / 3384

页数：8

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