Research on macro financial data classification method based on random forest algorithm
Yixin Liu · 2022 14th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) · 2022
In order to enhance the availability of macro financial data, it is necessary to accurately classify macro financial data. Therefore, a new macro financial data classification method based on random forest algorithm is proposed. Firstly, the macro financial data collection model is constructed in the form of triples to complete the macro financial data collection, and the characteristics of macro financial data are extracted according to the weak correlation characteristics between the data. After feature extraction, the classification sequence of macro financial data is obtained. Under the upper limit constraint of generalization error of the classifier, the random forest classification expression is constructed to complete the classification of macro financial data. The experimental results show that compared with the traditional classification methods, the proposed method improves the classification accuracy and reduces the classification time-consuming, indicating that the classification performance of the proposed method has been significantly enhanced.