Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction

作者：

Highlights：

• We propose a novel ensemble model for bankruptcy prediction.

• We use Extreme Gradient Boosting as an ensemble of decision trees.

• We propose a new approach for generating synthetic features to improve prediction.

• The presented method is evaluated on real-life data of Polish companies.

摘要

•We propose a novel ensemble model for bankruptcy prediction.•We use Extreme Gradient Boosting as an ensemble of decision trees.•We propose a new approach for generating synthetic features to improve prediction.•The presented method is evaluated on real-life data of Polish companies.

论文关键词：Bankruptcy prediction,Extreme gradient boosting,Synthetic features generation,Imbalanced data

论文评审过程：Received 26 January 2016, Revised 1 April 2016, Accepted 2 April 2016, Available online 6 April 2016, Version of Record 17 April 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.04.001