DocumentCode
2962394
Title
Evaluation of Residential Loan by Combining RVM and Logistic Regression
Author
Meng, Qinrong
Author_Institution
Financial Dept., Wuhan Univ. of Technol., Wuhan, China
fYear
2011
fDate
12-14 Aug. 2011
Firstpage
1
Lastpage
4
Abstract
A combining forecast model is proposed to evaluate the residential loan, which improves the accuracy of a single evaluation model. Firstly, the Relevance Vector Machine (RVM) model and logistic regression model are trained by the financial data respectively. Then the weighted average rule is used to fuse these two models based on a weight training procedure. Finally, the combining model is employed to evaluate the real house loan data. The experiments show that the combining evaluation modal is super to a single model and behaves robust.
Keywords
financial data processing; learning (artificial intelligence); regression analysis; RVM; combining forecast model; financial data; logistic regression model; real house loan data; relevance vector machine; residential loan evaluation; weight training procedure; weighted average rule; Accuracy; Data models; Logistics; Mathematical model; Predictive models; Support vector machines; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Management and Service Science (MASS), 2011 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-6579-8
Type
conf
DOI
10.1109/ICMSS.2011.5998124
Filename
5998124
Link To Document