Abstract
Based on the 2016–2020 China’s A-share listed companies as research samples, the model of random forests is constructed, from investors easier access to corporate performance and the related information of internal governance, to forecast the enterprise surplus control risk, and the prediction results compared with the traditional multiple linear regression model, the study found that compared with multiple linear regression model The random forest model has a better effect on enterprise earnings control risk prediction, which opens up a new way for the future application of machine learning research.
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Xue, R., Ding, H. (2022). Risk Prediction of Corporate Earnings Manipulation Based on Random Forest Model. In: Sugumaran, V., Sreedevi, A.G., Xu, Z. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. ICMMIA 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 136. Springer, Cham. https://doi.org/10.1007/978-3-031-05237-8_13
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DOI: https://doi.org/10.1007/978-3-031-05237-8_13
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