期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

基于决策树方法的银行客户信用评估 被引量：1

The Decision Tree Used to Evaluate the Trustworthiness of Customer
下载PDF
导出
摘要 分析了传统银行客户信用评估方法存在的问题,针对ID3算法存在的不足,提出了一种改进的ID3算法.实验结果表明,改进后的ID3算法分类正确率有所提高,所生成的决策树较为健壮、简洁,可以减少计算代价,提高计算效率. The article analyzeds the problem of traditional method for the evaluation of trustworthiness of customer and provideds an Advanced ID3 , Owing to some shortages in ID3. The experiment results show that the advanced ID3 not only has better true classification accuracy and can build stronger tree, but also can reduce the price of computation.
作者 王莉莉 刘同明 石亮 曹敢
机构地区 江苏科技大学电子信息学院
出处 《江南大学学报（自然科学版）》 CAS 2007年第6期816-820,共5页 Joural of Jiangnan University (Natural Science Edition)　
基金 江苏省教育厅青蓝工程资助项目(2005DX028J)
关键词 银行客户信用评估 决策树 ID3算法 the evaluation of trustworthiness of customer~ decision tree~ ID3
分类号 TP311.5 [自动化与计算机技术—计算机软件与理论]
  • 相关文献

参考文献12

  • 1石庆焱,靳云汇.个人信用评分的主要模型与方法综述[J].统计研究,2003,20(8):36-39. 被引量：38
  • 2Mehta M, Rissanen J, Agrawal R. MDL-based decision tree pruning [C]. Montreal,Canada: In: Int'l Conf on Knowledge Discovery in Database and Data Mining (KDD-95), 1995.
  • 3Mehta M, Agrawal R , Rissanen J. SLIQ: a fast scalable classifier for data mining [C]. Avignon, France: In Proc of The Fifth Int'l Conference on Extending Database Technology, 1996.
  • 4Sharer J, Agrawal R, Mehta M. SPRINT: a scalable parallel classifier for data mining[C]. Mumbai, India: In: 22 nd VLDB Conference, 1996.
  • 5Srivastava A, Singh V, Han E, et al. An efficient, scalable, parallel classifier for data mining [R]. Minneapolis, America:Technical Report TR-97010, University of Minnesota, 1997.
  • 6Gehrke J, Ramakrishnan R, Ganti V. Rainforest-a framework for fast decision tree construction of Large Datasets[C]. NewYork, Amrica : VLDB, 1998.
  • 7Alsabti K, Ranka S, Singh V. CLOUDS: a decision tree classifier for large datasets [C]. California, America: In 4th Intl, Conf on Knowledge Discovery and Data Mining, 1998.
  • 8Gehrke J, Ganti V, Ramakrishnan R, et al. BOAT-optimistic decision tree construction [C]. In Proceedings of SIGMOD, ACM. Pennsylvania: [s. n.],1999 :169-180.
  • 9Breiman L. Bagging predictors [J]. Machine Learning Journal, 1996,24(2) :123-140.
  • 10Quinlan J R. Induction of decision trees [J]. Machine Learning, 1986,1 ( 1 ) : 81-106.

二级参考文献10

  • 1Johnson, R. W. ( 1992). Legal, social and economic issues in implementing scoring in the US. In Credit Scoring and Credit Control, ed. L. C. Thomas, J. N. Crook, and D. B.Edelman. Oxford: Clarendon Press.
  • 2Joachimsthaler, E. A. and Stam, A. ( 1990 ). Mathematical programming approaches for the classification problem in two-group discriminant analysis. Multivariate Behavioural Research 25,427 - 454.
  • 3Henley, W. E. ( 1995 ) Statistical aspects of credit scoring.Unpublished PhD thesis, The Open University, Milton Keynes, UK.
  • 4Freed, N and Glover, F. ( 1981a). A linear programming approach to the discfiminant problems. Decision Sciences, 12,68 - 74.
  • 5Fitzpatrick, D. B. (1976) An analysis of bank credit card profit. Journal of Bank Research, 7,199 - 205.
  • 6Fisher, R. A. ( 1936). The use of multiple measurement in taxonomic problems, annuals of Eugenics 7,179 - 188.
  • 7Eisenbeis, R. A. (1979) Problems in applying discriminant analysis in credit scoring models. Journal of Banking and Finace, 2,205 - 219.
  • 8Eisenbeis, R. A. ( 1977 ) Pitfalls in the application of discriminant analysis in business, finance, and economics. The Journal of Finance, 32,875 - 900.
  • 9Durand, D. ( 1941 ) Risk elements in consumer installment financing. National Bureau of Economic Research, New York.
  • 10Davis, R. H., Edelman, D. B., and Gammermann, A. J.(1992) Machine-learning algorithms for credit-card applications. 1MA Journal of Mathematics Applied in Business and Industry,4,43 - 51.

共引文献37

同被引文献13

引证文献1

二级引证文献3

江南大学学报（自然科学版）
2007年 第6期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部