The best of two worlds: Balancing model strength and comprehensibility in business failure prediction using spline-rule ensembles
作者：
Highlights：
• Spline-rule ensembles are introduced to the domain of business failure prediction.
• The method uniquely reconciles performance and comprehensibility.
• A benchmark study demonstrates the technique's superior predictive performance.
• A case study exemplifies the method's instruments to deliver model insights.
摘要
•Spline-rule ensembles are introduced to the domain of business failure prediction.•The method uniquely reconciles performance and comprehensibility.•A benchmark study demonstrates the technique's superior predictive performance.•A case study exemplifies the method's instruments to deliver model insights.
论文关键词：Bankruptcy prediction,Business failure prediction,Data mining,Ensemble learning,Model comprehensibility,Penalized cubic regression splines,Rule ensembles,Spline-rule ensembles,Risk management
论文评审过程：Received 11 January 2017, Revised 17 June 2017, Accepted 23 July 2017, Available online 24 July 2017, Version of Record 9 August 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.07.036
