破产预测中期望最大化归算的平衡套袋——在罗马尼亚公司中的应用

Claudiu Clement
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引用次数: 0

摘要

破产预测模型被贷款机构、政策制定者或投资者广泛使用。尽管有大量的国际研究,但针对罗马尼亚公司特殊性的研究有限。平衡Bagging是一种集成方法,它对分类任务使用投票机制。期望最大化插值有助于替换缺失的数据。在这项研究中,我们报告了在超过20,000家罗马尼亚公司的数据集上,具有期望最大化Imputation的平衡装袋模型的有希望的准确性表现为90.03%。
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BALANCED BAGGING WITH EXPECTATION MAXIMIZATION IMPUTATION IN BANKRUPTCY PREDICTION – APPLICATION ON ROMANIAN COMPANIES
Bankruptcy prediction models are widely used by lending institutions, policy makers or investors. Despite the large volume of international research, limited studies have addressed the particularities of Romanian companies. Balanced Bagging is an Ensemble Method that uses a voting mechanism for a classification task. Expectation Maximization Imputation helps replacing the missing data. In this study we report a promising accuracy performance of 90.03% for the model of Balanced Bagging with Expectation Maximization Imputation on a dataset of more than 20,000 Romanian companies.
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