TY - GEN
T1 - Combined model of empirical study for credit risk management
AU - Han, Lu
AU - Han, Liyan
AU - Zhao, Hongwei
PY - 2010
Y1 - 2010
N2 - In this paper, we studied the two most commonly used artificial intelligence methods (Multilayer Perceptron and Radial Basis Function network) to build the credit scoring model of applications, and analyzed the most important restraining factors of the applications of neural network which is the exponential increase in the variables bringing the model over-complex. On this basis, the author combines econometric analysis of the experience, through logistic regression the model can filter the variables with a high degree of correlation, which greatly reduces the complexity of the model, while the model has a better explanation, and thus improve the effect of neural network prediction models. The method can also be used for a variety of artificial intelligence applications to improve forecast model results.
AB - In this paper, we studied the two most commonly used artificial intelligence methods (Multilayer Perceptron and Radial Basis Function network) to build the credit scoring model of applications, and analyzed the most important restraining factors of the applications of neural network which is the exponential increase in the variables bringing the model over-complex. On this basis, the author combines econometric analysis of the experience, through logistic regression the model can filter the variables with a high degree of correlation, which greatly reduces the complexity of the model, while the model has a better explanation, and thus improve the effect of neural network prediction models. The method can also be used for a variety of artificial intelligence applications to improve forecast model results.
KW - Credit risk
KW - Logistic regression
KW - Multilayer perceptron
KW - Neural networks
KW - Radial basis function
UR - https://www.scopus.com/pages/publications/78650275517
U2 - 10.1109/ICIFE.2010.5609281
DO - 10.1109/ICIFE.2010.5609281
M3 - 会议稿件
AN - SCOPUS:78650275517
SN - 9781424469253
T3 - Proceedings - 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010
SP - 189
EP - 192
BT - Proceedings - 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010
T2 - 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010
Y2 - 17 September 2010 through 19 September 2010
ER -