Machine learning models, epistemic set-valued data and generalized loss functions: An encompassing approach

dc.contributor.author	Couso Blanco, Inés
dc.contributor.author	Sánchez Ramos, Luciano
dc.date.accessioned	2017-02-01T07:40:08Z
dc.date.available	2017-02-01T07:40:08Z
dc.date.issued	2016
dc.identifier.citation	Information Sciences, 358-359, p. 129-150 (2016); doi:10.1016/j.ins.2016.04.016
dc.identifier.issn	0020-0255
dc.identifier.uri	http://hdl.handle.net/10651/39688
dc.description.sponsorship	The authors are grateful to two anonymous reviewers for their helpful comments. This work has been partially supported by the Spanish Ministry of Science and Innovation (MICINN) and the Regional Ministry of the Principality of Asturias under Grants TIN2014-56967-R and FC-15-GRUPIN14-073.
dc.format.extent	p. 129-150
dc.language.iso	eng
dc.relation.ispartof	Information Sciences
dc.rights	© 2016 Elsevier Inc.
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-84968572895&partnerID=40&md5=38d2ac3e0c5e4002f78865a67ce6675f
dc.title	Machine learning models, epistemic set-valued data and generalized loss functions: An encompassing approach
dc.type	journal article
dc.identifier.doi	10.1016/j.ins.2016.04.016
dc.relation.projectID	TIN2014-56967-R
dc.relation.projectID	FC-15-GRUPIN14-073
dc.relation.publisherversion	http://dx.doi.org/10.1016/j.ins.2016.04.016

Ficheros en el ítem

Ficheros	Tamaño	Formato	Ver
No hay ficheros asociados a este ítem.