DocumentCode
3037049
Title
A new credit scoring method based on improved fuzzy support vector machine
Author
Tang, Bo ; Qiu, Saibing
Author_Institution
Math. & Comput. Sci. Dept., Hunan City Univ., Yiyang, China
Volume
3
fYear
2012
fDate
25-27 May 2012
Firstpage
73
Lastpage
75
Abstract
The techniques of credit scoring are the effective measure for credit risk management, and research on credit scoring in China is meaningful. This paper has put forward the new thinking of the model of setting up the risk and scoring with the fuzzy support vector machine algorithm. The empirical results show that the algorithm is very practical, and it has good prediction accuracy and anti-noise ability.
Keywords
financial data processing; fuzzy set theory; risk management; support vector machines; SVM; anti-noise ability; credit risk management; credit scoring method; prediction accuracy; vector machine algorithm; Accuracy; Error analysis; Neural networks; Noise; Support vector machines; Training; credit scoring; fuzzy membership; fuzzy support vector machine;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Automation Engineering (CSAE), 2012 IEEE International Conference on
Conference_Location
Zhangjiajie
Print_ISBN
978-1-4673-0088-9
Type
conf
DOI
10.1109/CSAE.2012.6272911
Filename
6272911
Link To Document