Predicting Unseen Labels Using Label Hierarchies in Large-Scale Multi-label Learning

Abstract

An important problem in multi-label classification is to capture label patterns or underlying structures that have an impact on such patterns. One way of learning underlying structures over labels is to project both instances and labels into the same space where an instance and its relevant labels tend to have similar representations. In this paper, we… (More)
DOI: 10.1007/978-3-319-23528-8_7

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Cite this paper

@inproceedings{Nam2015PredictingUL, title={Predicting Unseen Labels Using Label Hierarchies in Large-Scale Multi-label Learning}, author={Jinseok Nam and Eneldo Loza Menc{\'i}a and Hyunwoo J. Kim and Johannes F{\"{u}rnkranz}, booktitle={ECML/PKDD}, year={2015} }