A Study of Accounting Teaching Feature Selection and Importance Assessment Based on Random Forest Algorithm

Online veröffentlicht: 03. Sept. 2024

Eingereicht: 15. Apr. 2024

Akzeptiert: 26. Juli 2024

DOI: https://doi.org/10.2478/amns-2024-2540

Schlüsselwörter

Behavioral data, Random forest, Feature selection, Gini index, Learning effect prediction, Accounting teaching

© 2024 Jing Hu., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.