Data analytic approach for bankruptcy prediction

作者：

Highlights：

• Features to predict a company’s bankruptcy have highly skewed distributions.

• A Box–Cox transformation is a powerful technique to remove skewness of data.

• Machine learning algorithms are more suitable for bankruptcy prediction than statistical models.

• By combining feature’s importance, we can understand the model.

摘要

•Features to predict a company’s bankruptcy have highly skewed distributions.•A Box–Cox transformation is a powerful technique to remove skewness of data.•Machine learning algorithms are more suitable for bankruptcy prediction than statistical models.•By combining feature’s importance, we can understand the model.

论文关键词：Bankruptcy prediction,Data analysis,Machine learning,Boosting,Preprocessing,Box–Cox transformation,Feature importance

论文评审过程：Received 5 July 2018, Revised 18 June 2019, Accepted 13 July 2019, Available online 15 July 2019, Version of Record 18 July 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.07.033