Personal Credit Rating Based on Partial Least Squares Regression Classification

2018 2nd International Workshop on Renewable Energy and Development

能源学;经济学

Ting-Ting, Dai^1 ; Chang-Ji, Shan^2 ; Yan-Shou, Dong^1 ; Yi-Duo, Bian^3

School of Mathematics and Statistics, Zhaotong University, Yunnan

657000, China^1

Institute of Physics and Information Engineering, Zhaotong University, Zhaotong, Yunnan

657000, China^2

School of Foreign Languages, Zhaotong University, Zhaotong, Yunnan

657000, China^3

关键词: Classification models;    Commercial bank;    Credit data;    Partial least square (PLS);    Partial least squares regression;    Personal credit;    Personal credit ratings;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/153/3/032017/pdf
DOI  :  10.1088/1755-1315/153/3/032017

来源: IOP

【 摘 要 】

In view of the current commercial bank credit issues, this paper proposes a personal credit assessment method based on partial least squares classification. The main idea of this method is: first, a matrix is made by quantifying the customer and the corresponding credit indicators; secondly, a partial least-squares regression classification model is established; and finally, a test is conducted using the German credit data in the model and the results are obtained. Simulation results show that this method is simple, feasible and effective.