RAPT improves multi-label label-set selection by retrieving similar documents and locally aggregating their thresholding outcomes to adapt per-instance cutoffs.
Artificial Intelligence170(16), 1175–1192 (Nov 2006)
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RAPT: Retrieval-Augmented Post-hoc Thresholding for Multi-Label Classification
RAPT improves multi-label label-set selection by retrieving similar documents and locally aggregating their thresholding outcomes to adapt per-instance cutoffs.