An Improved Multi-Class Support Vector Machine for Credit Scoring

摘要：

　　With the development of China”s economy,credit scoring has become important.The general credit scoring model is to solve the two classification problems,but in real life we often encounter multiple classification problems.This paper proposes a multi-class support vector machine based on genetic algorithm,which can solve multiple classification problems in the behavior assessment model.Genetic algorithm is used for support vector machine”s parameters optimization search.The parameters of SVM are coded into chromosomes with Gray code strategy.The empirical results show that the algorithm is very practical,and it has good prediction accuracy.

关键词： Credit scoring Multi-class support vector machine Genetic algorithm

作者: Bo TANG Min XIA Sai-Bing QIU

作者单位: Department of Mathematics and Computing Science,Hunan City University,Yiyang 413000,China Hunan Arts and Crafts Vocational College,Yiyang 413000,China

会议类型: 国内会议

会议名称: 2014年国际计算机科学与软件工程学术会议

会议地点: 杭州

会议语种:英文

页码: 1-6

在线出版日期: 2014-10-18（万方平台首次上网日期，不代表论文的发表时间）