A review of methods for imbalanced multi-label classification
Abstract: Highlights•Three types of imbalanced problems are common challenges in multi-label classification: imbalance within labels, between labels, and among label-sets.•A comprehensive and up-to-date review of methods for addressing imbalanced problems in multi-label classification is presented.•Methods for assessing imbalance level and performance measures in the multi-label scenario are surveyed.•Comparative analysis of the reviewed methods and their limitations are discussed to guide future directions.
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