All Mistakes Are Not Equal: Comprehensive Hierarchy Aware Multi-label Predictions (CHAMP). (arXiv:2206.08653v1 [cs.LG])

Web: http://arxiv.org/abs/2206.08653

This paper considers the problem of Hierarchical Multi-Label Classification
(HMC), where (i) several labels can be present for each example, and (ii)
labels are related via a domain-specific hierarchy tree. Guided by the
intuition that all mistakes are not equal, we present Comprehensive Hierarchy
Aware Multi-label Predictions (CHAMP), a framework that penalizes a
misprediction depending on its severity as per the hierarchy tree. While there
have been works that apply such an idea to single-label classification, to the
best of …

arxiv lg mistakes predictions