Self-paced Ensemble for Highly Imbalanced Massive Data Classification

@article{Liu2020SelfpacedEF,
  title={Self-paced Ensemble for Highly Imbalanced Massive Data Classification},
  author={Zhining Liu and Wei Cao and Zhifeng Gao and Jiang Bian and Hechang Chen and Yi Chang and Tie-Yan Liu},
  journal={2020 IEEE 36th International Conference on Data Engineering (ICDE)},
  year={2020},
  pages={841-852}
}
  • Zhining Liu, Wei Cao, +4 authors Tie-Yan Liu
  • Published 2020
  • Computer Science, Mathematics
  • 2020 IEEE 36th International Conference on Data Engineering (ICDE)
Many real-world applications reveal difficulties in learning classifiers from imbalanced data. The rising big data era has been witnessing more classification tasks with large-scale but extremely imbalance and low-quality datasets. Most of existing learning methods suffer from poor performance or low computation efficiency under such a scenario. To tackle this problem, we conduct deep investigations into the nature of class imbalance, which reveals that not only the disproportion between… Expand
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