An equivalence analysis of binary quantification methods

dc.contributor.author	Castaño Gutiérrez, Alberto
dc.contributor.author	Alonso González, Jaime
dc.contributor.author	González González, Pablo
dc.contributor.author	Coz Velasco, Juan José del
dc.date.accessioned	2023-10-25T08:54:46Z
dc.date.available	2023-10-25T08:54:46Z
dc.date.issued	2023
dc.identifier.isbn	978-157735880-0
dc.identifier.uri	https://hdl.handle.net/10651/69919
dc.description	AAAI Conference on Artificial Intelligence (37th. 2023. Washington, USA)
dc.description.sponsorship	This research has been funded by MINECO (the Spanish Ministerio de Economía y Competitividad), research project PID2019-110742RB-I00
dc.format.extent	p. 6944-6952
dc.language.iso	eng
dc.relation.ispartof	Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023
dc.rights	© 2023, Association for the Advancement of Artificial Intelligence
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167986894&partnerID=40&md5=c22fa2a54fe136ef4442f165db012cef
dc.title	An equivalence analysis of binary quantification methods
dc.type	conference output
dc.identifier.doi	10.1609/aaai.v37i6.25849
dc.relation.projectID	info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-110742RB-I00/ES/EXPLOTANDO EL CONOCIMIENTO DISPONIBLE PARA ADAPTAR Y APLICAR MODELOS APRENDIDOS A PARTIR DE DOMINIOS DIFERENTES/
dc.relation.publisherversion	https://doi.org/10.1609/aaai.v37i6.25849
dc.rights.accessRights	open access
dc.type.hasVersion	VoR

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