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Based on a set of credit card sample of Chinese commercial bank,a systemically comparative study of various statistical credit scoring models was firstly made in China The comparative study indicated that every model has its own strength and weakness The strengths of linear discriminant analysis,linear program,and Logistic regression are that these models are explainable and their outputs can be a linear scorecard(so can be easily implemented) But these models have higher misclassification rate comparing with others Neural network and classification tree models have a higher predict accuracy,but may be‘over fitted’,and their outputs are hard to be explained
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基本信息:
DOI：10.19343/j.cnki.11-1302/c.2004.06.009
中图分类号:F224
引用信息:
[1]石庆焱,靳云汇.多种个人信用评分模型在中国应用的比较研究[J].统计研究,2004(06):43-47.DOI:10.19343/j.cnki.11-1302/c.2004.06.009.
2004-06-15
2004-06-15