ASE: Anomaly scoring based ensemble learning for highly imbalanced datasets

Xiayu Liang, Ying Gao, Shanrong Xu

Abstract: Highlights•Introduce a scoring system based on anomaly detection to the resampling strategy.•The proposed weighting functions are intuitive and easy to understand.•Propose an efficient ensemble learning framework.•Excellent performance on different real-world imbalanced classification tasks.