Research on the combined model of corporate failure prediction

Zhou Xu

doi:10.1117/12.2615104

15 October 2021 Research on the combined model of corporate failure prediction

Zhou Xu

Proceedings Volume 11933, 2021 International Conference on Neural Networks, Information and Communication Engineering; 119332M (2021) https://doi.org/10.1117/12.2615104
Event: 2021 International Conference on Neural Networks, Information and Communication Engineering, 2021, Qingdao, China

Abstract

Corporate failure prediction is based on the extraction of key factors and early warning based on factor indicators or characteristic variables related to corporate failure. The current representative failure prediction empirical models include Credit Scoring, DA, MDA, and so on. However, the above models have problems such as data deviation and uncertain factor contributions. It is to explore starting from the machine learning model, establishing a combined model, combining the minimum variance method, to construct the Logistic-SVM combined model. The study found that the total classification accuracy of the Logistic-SVM combined model is higher than that of the traditional single model, and the error rate is also lower.

Citation Download Citation

Zhou Xu "Research on the combined model of corporate failure prediction", Proc. SPIE 11933, 2021 International Conference on Neural Networks, Information and Communication Engineering, 119332M (15 October 2021); https://doi.org/10.1117/12.2615104

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