Improving Michigan-style fuzzy-rule base classification generation using a Choquet-like Copula-based aggregation function

dc.contributor.authorHinojosa-Cardenas, Edward
dc.contributor.authorSarmiento-Calisaya, Edgar
dc.contributor.authorCamargo, Heloisa A.
dc.contributor.authorSanz Delgado, José Antonio
dc.contributor.departmentEstadística, Informática y Matemáticases_ES
dc.contributor.departmentEstatistika, Informatika eta Matematikaeu
dc.contributor.funderUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, PJUPNA1926es
dc.date.accessioned2022-03-10T08:00:00Z
dc.date.available2022-03-10T08:00:00Z
dc.date.issued2021
dc.description.abstractThis paper presents a modification of a Michigan-style fuzzy rule based classifier by applying the Choquet-like Copula-based aggregation function, which is based on the minimum t-norm and satisfies all the conditions required for an aggregation function. The proposed new version of the algorithm aims at improving the accuracy in comparison to the original algorithm and involves two main modifications: replacing the fuzzy reasoning method of the winning rule by the one based on Choquet-like Copula-based aggregation function and changing the calculus of the fitness of each fuzzy rule. The modification proposed, as well as the original algorithm, uses a (1+1) evolutionary strategy for learning the fuzzy rulebase and it shows promising results in terms of accuracy, compared to the original algorithm, over ten classification datasets with different sizes and different numbers of variables and clases.en
dc.description.sponsorshipThis work was supported by the Universidad Nacional de San Agustin de Arequipa under Project IBAIB-06-2019-UNSA and in part by the Spanish Ministry of Economy and Competitiveness through the Spanish National Research (project PID2019-108392GB-I00 / AEI / 10.13039/501100011033) and by the Public University of Navarre under the project PJUPNA1926.en
dc.format.extent9 p.
dc.format.mimetypeapplication/pdfen
dc.format.mimetypeapplication/zipen
dc.identifier.issn1613-0073
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/42490
dc.language.isoengen
dc.publisherCEUR Workshop Proceedings (CEUR-WS.org)en
dc.relation.ispartofWILF’21: The 13th International Workshop on Fuzzy Logic and Applications, Dec. 20–22, 2021, Vietri sul Mare, Italyen
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108392GB-I00/ES/
dc.rights© 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).en
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectMichigan-style algorithmen
dc.subjectFuzzy rule-based classification systemsen
dc.subjectChoquet-like copula-based aggregation functionen
dc.subjectEvolutionary strategyen
dc.titleImproving Michigan-style fuzzy-rule base classification generation using a Choquet-like Copula-based aggregation functionen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dspace.entity.typePublication
relation.isAuthorOfPublication04db2b7d-89dc-4815-be4a-4b201cdce99b
relation.isAuthorOfPublication.latestForDiscovery04db2b7d-89dc-4815-be4a-4b201cdce99b

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