A dual evolutionary bagging for class imbalance learning

作者：

Highlights：

• A dual-ensemble framework for class imbalanced datasets is constructed.

• Optimizing the base classifier for each sub-dataset in inner ensemble.

• Multi-modal genetic algorithm is employed to seek the optimal ensemble model.

摘要

•A dual-ensemble framework for class imbalanced datasets is constructed.•Optimizing the base classifier for each sub-dataset in inner ensemble.•Multi-modal genetic algorithm is employed to seek the optimal ensemble model.

论文关键词：Imbalance learning,Multi-modal genetic algorithm,Oversampling,Ensemble structure

论文评审过程：Received 25 January 2022, Revised 25 May 2022, Accepted 9 June 2022, Available online 17 June 2022, Version of Record 23 June 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117843