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Enhancing soft computing techniques to actively address imbalanced regression problems

dc.contributor.authorArteaga, María
dc.contributor.authorGacto Colorado, María José
dc.contributor.authorGalende, Marta
dc.contributor.authorAlcalá Fernández, Jesús 
dc.contributor.authorAlcalá Fernández, Rafael 
dc.date.accessioned2023-09-07T09:38:52Z
dc.date.available2023-09-07T09:38:52Z
dc.date.issued2023-12-30
dc.identifier.citationMaría Arteaga, María José Gacto, Marta Galende, Jesús Alcalá-Fdez, Rafael Alcalá, Enhancing soft computing techniques to actively address imbalanced regression problems, Expert Systems with Applications, Volume 234, 2023, 121011, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2023.121011.es_ES
dc.identifier.urihttps://hdl.handle.net/10481/84310
dc.description.sponsorshipThis paper has been supported in part by the ERDF A way of making Europe/Health Institute Carlos III/Spanish Ministry of Science, Innovation and Universities (grant number PI20/00711), by the ERDF A way of making Europe/Regional Government of Andalusia/Ministry of Economic Transformation, Industry, Knowledge and Universities (grant numbers P18-RT-2248 and B-CTS-536-UGR20) and by the MCIN/AEI/10.13039/50110001103 (grant numbers PID2019-107793GB-I00 and PID2020-119478GB-I00). Funding for open access charge: Universidad de Granada / CBUA .es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectImbalanced regressiones_ES
dc.subjectMulti-objective evolutionary algorithmses_ES
dc.subjectFuzzy rule-based systemses_ES
dc.titleEnhancing soft computing techniques to actively address imbalanced regression problemses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.1016/j.eswa.2023.121011
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES


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