TY - GEN
T1 - Discrimination for non-performing loans recovery
T2 - A method of support vector machines based on wavelet transform
AU - He, Ming
AU - Liu, Ning
AU - Xia, Enjun
PY - 2010
Y1 - 2010
N2 - According to the complexity of financial system, the model of discrimination for non-performing loans recovery based on support vector machines(SVM) and wavelet transform integrated is proposed, which in order to improve the accuracy and reliability of risk assessment. First we performed model input optimization using the wavelet transform, and then selected the radial basis function(RBF) as the kernel function of wavelet-SVM, At last, we compared with the original SVM, experimental results show that the method is a feasible and effective recognition method with higher generalization performance.
AB - According to the complexity of financial system, the model of discrimination for non-performing loans recovery based on support vector machines(SVM) and wavelet transform integrated is proposed, which in order to improve the accuracy and reliability of risk assessment. First we performed model input optimization using the wavelet transform, and then selected the radial basis function(RBF) as the kernel function of wavelet-SVM, At last, we compared with the original SVM, experimental results show that the method is a feasible and effective recognition method with higher generalization performance.
KW - non-performing loans recovery
KW - radial basis function
KW - support vector machines
KW - wavelet transform
UR - https://www.scopus.com/pages/publications/79961179626
U2 - 10.1109/ISISE.2010.20
DO - 10.1109/ISISE.2010.20
M3 - Conference contribution
AN - SCOPUS:79961179626
SN - 9780769543604
T3 - Proceedings - 3rd International Symposium on Information Science and Engineering, ISISE 2010
SP - 88
EP - 92
BT - Proceedings - 3rd International Symposium on Information Science and Engineering, ISISE 2010
PB - IEEE Computer Society
ER -