Self-paced Ensemble for Highly Imbalanced Massive Data Classification

Zhining Liu
Zhining Liu
Wei Cao
Wei Cao
Zhifeng Gao
Zhifeng Gao
Jiang Bian
Jiang Bian
Yi Chang
Yi Chang

ICDE, pp. 841-852, 2020.

Cited by: 11|Views73
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Abstract:

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 sc...More
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