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Listed companies' financial distress prediction based on weighted majority voting combination of multiple classifiers

机译:基于多个分类器的加权多数投票组合的上市公司财务困境预测

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摘要

How to effectively predict financial distress is an important problem in corporate financial management. Though much attention has been paid to financial distress prediction methods based on single classifier, its limitation of uncertainty and benefit of multiple classifier combination for financial distress prediction has also been neglected. This paper puts forward a financial distress prediction method based on weighted majority voting combination of multiple classifiers. The framework of multiple classifier combination system, model of weighted majority voting combination, basic classifiers' voting weight model and basic classifiers' selection principles are discussed in detail. Empirical experiment with Chinese listed companies' real world data indicates that this method can greatly improve the average prediction accuracy and stability, and it is more suitable for financial distress prediction than single classifiers.
机译:如何有效地预测财务困境是企业财务管理中的重要问题。尽管基于单分类器的财务困境预测方法受到了广泛的关注,但其不确定性的局限性以及使用多个分类器组合进行财务困境预测的益处也被忽略。提出了一种基于多个分类器的加权多数投票组合的财务困境预测方法。详细讨论了多分类器组合系统的框架,加权多数表决组合模型,基本分类器的投票权重模型和基本分类器的选择原则。通过对中国上市公司真实数据的实证实验表明,该方法可以大大提高平均预测的准确性和稳定性,比单一分类器更适合财务困境的预测。

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