Show simple item record

dc.contributor.authorGouk, Henryen_NZ
dc.contributor.authorPfahringer, Bernharden_NZ
dc.contributor.authorCree, Michael J.en_NZ
dc.contributor.editorDurrant, Bob
dc.contributor.editorKim, Kee-Eung
dc.coverage.spatialHamiltonen_NZ
dc.date.accessioned2017-02-16T23:34:41Z
dc.date.available2016en_NZ
dc.date.available2017-02-16T23:34:41Z
dc.date.issued2016en_NZ
dc.identifier.citationGouk, H., Pfahringer, B., & Cree, M. J. (2016). Learning Distance Metrics for Multi-Label Classification. In B. Durrant & K.-E. Kim (Eds.), Proceedings of The 8th Asian Conference on Machine Learning (Vol. 63, pp. 318–333).en
dc.identifier.urihttp://hdl.handle.net/10289/10898
dc.description.abstractDistance metric learning is a well studied problem in the field of machine learning, where it is typically used to improve the accuracy of instance based learning techniques. In this paper we propose a distance metric learning algorithm that is specialised for multi-label classification tasks, rather than the multiclass setting considered by most work in this area. The method trains an embedder that can transform instances into a feature space where squared Euclidean distance provides an estimate of the Jaccard distance between the corresponding label vectors. In addition to a linear Mahalanobis style metric, we also present a nonlinear extension that provides a substantial boost in performance. We show that this technique significantly improves upon current approaches for instance based multi-label classification, and also enables interesting data visualisations.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.relation.urihttp://www.jmlr.org/proceedings/papers/v63/Gouk8.pdf
dc.rights© 2016 H. Gouk, B. Pfahringer & M. Cree.
dc.source8th Asian Conference on Machine Learningen_NZ
dc.subjectDistance Metric Learning
dc.subjectMulti-Label Classification
dc.subjectInstance Based Learning
dc.titleLearning Distance Metrics for Multi-Label Classificationen_NZ
dc.typeConference Contribution
dc.relation.isPartOfProceedings of The 8th Asian Conference on Machine Learningen_NZ
pubs.begin-page318
pubs.elements-id191719
pubs.end-page333
pubs.finish-date2016-11-18en_NZ
pubs.organisational-group/Waikato
pubs.organisational-group/Waikato/FCMS
pubs.organisational-group/Waikato/FCMS/2018 PBRF - FCMS
pubs.organisational-group/Waikato/FCMS/Computer Science
pubs.organisational-group/Waikato/FCMS/Computer Science/ML Group
pubs.organisational-group/Waikato/FSEN
pubs.organisational-group/Waikato/FSEN/2018 PBRF - FSEN
pubs.organisational-group/Waikato/FSEN/Engineering
pubs.publisher-urlhttp://www.acml-conf.org/2016/en_NZ
pubs.start-date2016-11-16en_NZ
pubs.volume63en_NZ


Files in this item

This item appears in the following Collection(s)

Show simple item record