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机构地区:[1]重庆大学数理学院 [2]重庆大学统计与工商管理学院
出 处:《统计研究》2005年第11期29-31,共3页Statistical Research
摘 要:In this paper, a new method based on LS-SVM (Least Squares Support Vector Machines) is presented to deal with credit assessment in commercial banks for solving the problem of inadequate samples of the financial data,which usually happended in most banks in China.On the basis of SLT(Statistical Learning Theory),this approach with methodology of SRM (Structural Risk Minimization)will overcome the shortcomings of traditional credit assessment models,such as over fitting and local optimization,and,by using kernel functions in model,it will effectively solve the problems of linear inseparability and selecting parameters of model.The approach has some good properties including a generalization ability and global optimization in terms of sample processing.It is a new way for the credit assessment on the condition of small samples from bank data.The feasibility,effectiveness and practicability of presented approach was verified by experiments.In this paper, a new method based on LS-SVM (Least Squares Support Vector Machines) is presented to deal with credit assessment in commercial banks for solving the problem of inadequate samples of the financial data, which usually happended in most banks in China. On the basis of SLT (Statistical Learning Theory), this approach with methodology of SRM (Structural Risk Minimization)wiU overcome the shortcomings of traditional credit assessment models, such as over fitting and local optimization, and, by using kernel functions in model, it will effectively solve the problems of linear inseparability and selecting parameters of model. The approach has some good properties including a generalization ability and global optimization in terms of sample processing. It is a new way for the credit assessment on the condition of small samples from bank data. The feasibility, effectiveness and practicability of presented approach was verified by experiments.
关 键 词:信用评价系统 个人消费贷款 国内商业银行 零售业务 风险管理 消费信贷 住房按揭 汽车贷款 教育贷款 组成部分
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