Research Article
Comparison of Decision Trees and Deep Learning in Personal Credit Classification
@INPROCEEDINGS{10.4108/eai.2-12-2022.2328732, author={Yunteng Li}, title={Comparison of Decision Trees and Deep Learning in Personal Credit Classification}, proceedings={Proceedings of the 3rd International Conference on Big Data Economy and Information Management, BDEIM 2022, December 2-3, 2022, Zhengzhou, China}, publisher={EAI}, proceedings_a={BDEIM}, year={2023}, month={6}, keywords={personal credit; categorical prediction; decision tree; deep learning}, doi={10.4108/eai.2-12-2022.2328732} }- Yunteng Li
Year: 2023
Comparison of Decision Trees and Deep Learning in Personal Credit Classification
BDEIM
EAI
DOI: 10.4108/eai.2-12-2022.2328732
Abstract
The rapid development of the financial industry makes the financial institutions facing severe credit risk problems. The accurate classification of users' credit rating can help banks avoid potential risks and reduce losses. Based on this, this paper makes a compar-ative study on the application performance of two typical algorithms in the field of ma-chine learning - decision tree and deep learning in bank customer classification. It is found that the decision tree algorithm is suitable for data sets with small amount of data and discrete characteristics while deep learning algorithm is more suitable for the situa-tion of huge amount of data, and has better performance in dealing with the continuity problem.
Copyright © 2022–2024 EAI