Multi-label sampling based on local label imbalance

Liu Bin,Blekas Konstantinos,Tsoumak Grigorios

Pattern Recognition（2022）

引用 18|浏览43

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摘要

•The local imbalance is more crucial than the global one in multi-label data.•The local imbalance based measure assesses the hardness of multi-label data.•MLSOL and MLUL tackle the multi-label class imbalance issue via local imbalance.•Suitable application situations of our two methods are identified, respectively.

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关键词

Multi-label learning,Class imbalance,Oversampling and undersampling,Local label imbalance,Ensemble methods

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