Do all roads lead to Rome? Studying distance measures in the context of machine learning

Blanco Mallo, E.; Morán Fernández, L.; Remeseiro López, Beatriz; Bolón Canedo, V.

doi:10.1016/j.patcog.2023.109646

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Do all roads lead to Rome? Studying distance measures in the context of machine learning

dc.contributor.author	Blanco Mallo, E.
dc.contributor.author	Morán Fernández, L.
dc.contributor.author	Remeseiro López, Beatriz
dc.contributor.author	Bolón Canedo, V.
dc.date.accessioned	2023-10-25T08:55:08Z
dc.date.available	2023-10-25T08:55:08Z
dc.date.issued	2023
dc.identifier.citation	Pattern Recognition, 141 (2023); doi:10.1016/j.patcog.2023.109646
dc.identifier.issn	0031-3203
dc.identifier.uri	https://hdl.handle.net/10651/69967
dc.description.sponsorship	This work has been supported by the National Plan for Scientific and Technical Research and Innovation of the Spanish Government (Grant PID2019-109238GB, subprojects C21 and C22), by the Spanish Ministry of Science and Innovation (Grant FPI PRE2020-092608), and by the Xunta de Galicia (Grant ED431C 2022/44) with the European Union ERDF funds. CITIC, as Research Center accredited by Galician University System, is funded by “Consellería de Cultura, Educación e Universidades from Xunta de Gali- cia”, supported in an 80% through ERDF Funds, ERDF Operational Programme Galicia 2014-2020, and the remaining 20% by “Secretaría Xeral de Universidades” (Grant ED431G 2019/01).
dc.language.iso	eng
dc.relation.ispartof	Pattern Recognition
dc.rights	© 2023 The Authors.
dc.rights	CC Reconocimiento – No Comercial – Sin Obra Derivada 4.0 Internacional
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158888609&doi=10.1016%2fj.patcog.2023.109646&partnerID=40&md5=81a1d7417de0477ea7bd7a191d574846
dc.title	Do all roads lead to Rome? Studying distance measures in the context of machine learning
dc.type	journal article
dc.identifier.doi	10.1016/j.patcog.2023.109646
dc.relation.projectID	info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-109238GB-C21/ES/SISTEMAS DE RECOMENDACION EXPLICABLES/
dc.relation.projectID	PRE2020-092608
dc.relation.projectID	info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-109238GB-C22/ES/APRENDIZAJE AUTOMATICO ESCALABLE Y EXPLICABLE/
dc.relation.publisherversion	http://dx.doi.org/10.1016/j.patcog.2023.109646
dc.rights.accessRights	open access
dc.type.hasVersion	VoR

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