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dc.contributor.author郭振亚
dc.date.accessioned2016-07-01T08:34:50Z
dc.date.available2016-07-01T08:34:50Z
dc.date.issued2009
dc.identifier.citation电脑知识与技术,2009,(7):135-137
dc.identifier.issn1009-3044
dc.identifier.otherDNZS200907053
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/127179
dc.description.abstract信用卡业务现在是银行很重要的资产业务,构建一个适用的个人信用评估模型十分重要。基于近年来在智能学习系统领域发展起来的新理论,引入小样本学习的通用学习算法——支持向量机(SVM),建立了个人信用评估模型,通过与神经网络模型的比较,证实了该方法用于信用卡个人信用评估的有效性及优越性。
dc.description.abstractCredit card business is an important asset business in the bank,to construct a suitable personal credit evaluation model is very im-portant.Based on the recent development in the field of intelligent system of the new theory,introduced the general learning small sample learning algorithm: support vector machine(SVM) to establish the individual credit evaluation model,through the comparison with the neu-ral network model,This method proves to be used to evaluate the personal credit card superiority and effectively.
dc.language.isozh_CN
dc.subject信用卡个人信用评估
dc.subject支持向量机
dc.subject分类
dc.subjectcredit card evaluation
dc.subjectSVM
dc.subjectClassification
dc.title支持向量机在信用卡信用评估的应用
dc.title.alternativeUsing Support Vector Machine for the Credit Evaluation
dc.typeArticle


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