%0 Journal Article
%T Five-category classification of loan risk based on integration of rough sets and neural network<br>基于粗糙集和神经网络集成的贷款风险5级分类
%A KE Kong-lin
%A FENG Zong-xian
%A <br>柯孔林
%A 冯宗宪
%J 控制理论与应用
%D 2008
%I 
%X An integrated model of rough set and neural network for five-category classification of loan risk is proposed. The financial data are discretized by using the self-organizing mapping neural network;and the evaluation indices are reduced without information loss through a genetic algorithm.The reduced indices are used to develop the rules for the five-category classification of loan risk,and to train the neural network.The rough set theory is used to determine the category for the test sample which matches all rules in the rule-base.The neural network is applied to separate those test samples which do not match any one rule in the rule-base.698 loan finns of five-category are selected as test samples. The prediction accuracy of the integrated model combining rough sets and neural network is 82.07%.This verifies the effectiveness of our approach.
%K rough set theory
%K neural network
%K loan risk
%K classification<br>粗糙集理论
%K 神经网络
%K 贷款风险
%K 分类
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=282D14B9EECB371CAD85C38B7BB0D1D1&yid=67289AFF6305E306&vid=C5154311167311FE&iid=E158A972A605785F&sid=61000B595C9AE527&eid=50FF665B2730AEEC&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=2&reference_num=7