A focal-aware cost-sensitive boosted tree for imbalanced credit scoring

作者：

Highlights：

• A cost-sensitive LightGBM is proposed for imbalanced credit scoring.

• Focal loss is embedded to transform LightGBM into a cost-sensitive version.

• We corroborate the validity of the algorithm by interpreting the results.

• Feature importance globally interprets the prediction results of LightGBM-focal.

• PDP tool locally interprets the credit scoring of LightGBM-focal.

摘要

•A cost-sensitive LightGBM is proposed for imbalanced credit scoring.•Focal loss is embedded to transform LightGBM into a cost-sensitive version.•We corroborate the validity of the algorithm by interpreting the results.•Feature importance globally interprets the prediction results of LightGBM-focal.•PDP tool locally interprets the credit scoring of LightGBM-focal.

论文关键词：Credit scoring,Cost-sensitive,LightGBM,Interpretability

论文评审过程：Received 5 January 2022, Revised 5 July 2022, Accepted 11 July 2022, Available online 16 July 2022, Version of Record 20 July 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118158