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Online Boosting Algorithms for Multi-label Ranking

We consider the multi-label ranking approach to multi-label learning. Boosting is a natural method for multi-label ranking as it aggregates weak predictions through majority votes, which can be directly used as scores to produce a ranking of the labels.

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Cite this as

Young Hun Jung, Ambuj Tewari (2025). Dataset: Online Boosting Algorithms for Multi-label Ranking. https://doi.org/10.57702/ktkum9xh

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Additional Info

Field	Value
Created	January 2, 2025
Last update	January 2, 2025
Defined In	https://doi.org/10.48550/arXiv.1710.08079
Author	Young Hun Jung
More Authors	Ambuj Tewari