Research Area: Machine Learning
To explore the enterprise credit risk evaluation, the application effect of several common neural network models in Chinese small and medium-sized enterprise data sets was compared and the optimal parameters for each model were determined. In addition, the classification accuracy and the applicability of the model were compared, and finally the common problem of optimization neural network algorithm based on population was solved: need to determine the dimensions in advance. The experimental results showed that the probabilistic neural network (PNN) had the minimum error rate and second types of errors, while the PNN model had the highest AUC value and was robust. To sum up, the algorithm makes some contributions to solve the financing problem of small and medium-sized enterprises in China.
Keywords:
Credit Risk Evaluation
Neural Network Algorithm
Machine Learning
Deep Learning
Author(s) Name: Xiaobing Huang,Xiaolian and Liu Yuanqian Ren
Journal name: Cognitive Systems Research
Conferrence name:
Publisher name: ELSEVIER
DOI: 10.1016/j.cogsys.2018.07.023
Volume Information: Volume 52, December 2018, Pages 317-324
