Issuing a going‐concern opinion is a difficult and complex task for auditors. The auditors have to take into account different critical factors in order to make the right decision based on information obtained from the auditing process. This study adopts the so‐called “random forest” approach (based on the ensemble method) to assist auditors in making such a decision. To investigate the corresponding effect of the proposed approach, we conduct a series of experiments and a performance comparison. The results show that the random forest method outperforms the baseline methods in terms of the accuracy rate, ROC area, kappa value, type II error, precision, and recall rate. The proposed approach is proven to be more accurate and stable than previous methods.

中文翻译：

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公司持续经营状况评估：基于集成框架的模型

出具持续经营意见对审计师来说是一项艰巨而复杂的任务。审计师必须考虑不同的关键因素，以便根据从审计过程中获得的信息做出正确的决定。本研究采用所谓的“随机森林”方法（基于集成方法）来协助审计师做出这样的决定。为了研究所提出方法的相应效果，我们进行了一系列实验和性能比较。结果表明，随机森林方法在准确率、ROC 面积、kappa 值、II 类错误、精度和召回率方面优于基线方法。所提出的方法被证明比以前的方法更准确和稳定。