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Nearest labelset using double distances for multi-label classification

Multi-label classification is a type of supervised learning where an instance may belong to multiple labels simultaneously. Predicting each label independently has been criticized for not exploiting any correlation between labels. In this article we propose a novel approach, Nearest Labelset using D...

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Detalles Bibliográficos
Autores principales: Gweon, Hyukjun, Schonlau, Matthias, Steiner, Stefan H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924696/
https://www.ncbi.nlm.nih.gov/pubmed/33816895
http://dx.doi.org/10.7717/peerj-cs.242

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