Research Article
Design of Enterprise Financial and Economic Data Accurate Classification Management System Based on Random Forest
@INPROCEEDINGS{10.1007/978-3-031-18123-8_22, author={Junlin Li and Haonan Chu}, title={Design of Enterprise Financial and Economic Data Accurate Classification Management System Based on Random Forest}, proceedings={Multimedia Technology and Enhanced Learning. 4th EAI International Conference, ICMTEL 2022, Virtual Event, April 15-16, 2022, Proceedings}, proceedings_a={ICMTEL}, year={2022}, month={10}, keywords={Random forest Financial data Management system Data classification}, doi={10.1007/978-3-031-18123-8_22} }- Junlin Li
Haonan Chu
Year: 2022
Design of Enterprise Financial and Economic Data Accurate Classification Management System Based on Random Forest
ICMTEL
Springer
DOI: 10.1007/978-3-031-18123-8_22
Abstract
The conventional system has the problems of low recall rate, accuracy rate and high false positive rate of financial data classification. Therefore, an accurate classification management system of enterprise financial and economic data based on random forest is proposed. In the hardware, the front end, middle layer, server end and enterprise financial and economic data display end are used to form the overall architecture of the system, optimize the data memory of the server end, and transform the serial communication circuit of the development board; In the software design, abnormal financial data are filtered, a decision tree is established for each sample data, the utility function value is learned through the membership of the decision tree, and the optimal classification category is selected for the data through the random forest classifier. The experimental results show that the designed system improves the recall and accuracy of data classification, reduces the false positive rate, and the financial data classification results are more accurate and reliable.
