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An equivalence analysis of binary quantification methods

dc.contributor.authorCastaño Gutiérrez, Alberto 
dc.contributor.authorAlonso González, Jaime 
dc.contributor.authorGonzález González, Pablo 
dc.contributor.authorCoz Velasco, Juan José del 
dc.date.accessioned2023-10-25T08:54:46Z
dc.date.available2023-10-25T08:54:46Z
dc.date.issued2023
dc.identifier.isbn978-157735880-0
dc.identifier.urihttps://hdl.handle.net/10651/69919
dc.descriptionAAAI Conference on Artificial Intelligence (37th. 2023. Washington, USA)
dc.description.sponsorshipThis research has been funded by MINECO (the Spanish Ministerio de Economía y Competitividad), research project PID2019-110742RB-I00
dc.format.extentp. 6944-6952
dc.language.isoeng
dc.relation.ispartofProceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023
dc.rights© 2023, Association for the Advancement of Artificial Intelligence
dc.sourceScopus
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85167986894&partnerID=40&md5=c22fa2a54fe136ef4442f165db012cef
dc.titleAn equivalence analysis of binary quantification methods
dc.typeconference output
dc.identifier.doi10.1609/aaai.v37i6.25849
dc.relation.projectIDinfo: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.publisherversionhttps://doi.org/10.1609/aaai.v37i6.25849
dc.rights.accessRightsopen access
dc.type.hasVersionVoR


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