DocumentCode :
3520596
Title :
Recombining Forecasts Used in Personal Credit Scoring
Author :
Ming-hui, Jiang ; Yu-fang, Chen
Author_Institution :
Sch. of Manage., Harbin Inst. of Technol.
fYear :
2006
fDate :
5-7 Oct. 2006
Firstpage :
1719
Lastpage :
1722
Abstract :
Using the idea of combining forecasts, this paper presents a new approach by combining multi-linear regression and logistic with three different NNs. Then, recombine them with perceptron and apply it in personal credit scoring of one commercial bank. The results indicate that the combining methods are more accurate than either of the individual technology, and recombining is a reasonable way because it has greater precision than either the combining methods or pre-combining models, especially in avoiding recognizing the bad applications as good ones
Keywords :
economic forecasting; financial data processing; perceptrons; regression analysis; NN perceptron; logistic regression; multilinear regression; neural networks; personal credit scoring forecasts; Artificial intelligence; Artificial neural networks; Classification tree analysis; Economic forecasting; Environmental economics; Logistics; Neural networks; Predictive models; Statistics; Technology forecasting; Logistic regression; Multi-linear regression; Personal credit risk scoring; Recombining forecast;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Management Science and Engineering, 2006. ICMSE '06. 2006 International Conference on
Conference_Location :
Lille
Print_ISBN :
7-5603-2355-3
Type :
conf
DOI :
10.1109/ICMSE.2006.314067
Filename :
4105171
Link To Document :
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