An improvement to the classification based on the measurement of the similarity quality using fuzzy relations

The learning of classification rules is a classic problem of the automatic learning. The algorithm IRBASIR for the induction of classification rules based on similaridad relations allows to discover knowledge starting from decision systems that contain features with continuous and discrete domains....

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Autores:
Fernandez Hernandez, Yumilka Barbara
Filiberto, Yaima
Frias, Mabel
Bello, Rafael
Caballero, Yaile
Tipo de recurso:
Article of journal
Fecha de publicación:
2015
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/60647
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/60647
http://bdigital.unal.edu.co/58979/
Palabra clave:
62 Ingeniería y operaciones afines / Engineering
classification rules
fuzzy sets
similarity relations
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
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spelling Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Fernandez Hernandez, Yumilka Barbara53226f15-d0cb-44b7-865e-8061c144f1f3300Filiberto, Yaima8e86736f-c149-407c-ab53-5cf564595b67300Frias, Mabeld8c900e6-75bc-4578-8834-a3fd8fa5616a300Bello, Rafael61ecea12-34d0-41c1-816a-1b4769cbc52e300Caballero, Yaile8055fafc-ef24-4109-af2a-d6be9fd4202b3002019-07-02T18:47:41Z2019-07-02T18:47:41Z2015-09-01ISSN: 2346-2183https://repositorio.unal.edu.co/handle/unal/60647http://bdigital.unal.edu.co/58979/The learning of classification rules is a classic problem of the automatic learning. The algorithm IRBASIR for the induction of classification rules based on similaridad relations allows to discover knowledge starting from decision systems that contain features with continuous and discrete domains. This algorithm has shown to obtain higher results than other well-known algorithms. In this article, several modifications to this algorithm based on the Fuzzy sets theory are proposed, taking into account the measure quality of similarity. The experimental results show that using the fuzzy sets theory allow to obtain higher results than the original algorithm.application/pdfspaUniversidad Nacional de Colombia (Sede Medellín). Facultad de Minas.https://revistas.unal.edu.co/index.php/dyna/article/view/45989Universidad Nacional de Colombia Revistas electrónicas UN DynaDynaFernandez Hernandez, Yumilka Barbara and Filiberto, Yaima and Frias, Mabel and Bello, Rafael and Caballero, Yaile (2015) An improvement to the classification based on the measurement of the similarity quality using fuzzy relations. DYNA, 82 (193). pp. 70-76. ISSN 2346-218362 Ingeniería y operaciones afines / Engineeringclassification rulesfuzzy setssimilarity relationsAn improvement to the classification based on the measurement of the similarity quality using fuzzy relationsArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTORIGINAL45989-263859-2-PB.pdfapplication/pdf439439https://repositorio.unal.edu.co/bitstream/unal/60647/1/45989-263859-2-PB.pdffa99ad5f4ace7c1407fba82b207dd94aMD51THUMBNAIL45989-263859-2-PB.pdf.jpg45989-263859-2-PB.pdf.jpgGenerated Thumbnailimage/jpeg9398https://repositorio.unal.edu.co/bitstream/unal/60647/2/45989-263859-2-PB.pdf.jpg479acfbb5cd5d1dd4b9382627f79208fMD52unal/60647oai:repositorio.unal.edu.co:unal/606472023-04-08 23:04:39.072Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co
dc.title.spa.fl_str_mv An improvement to the classification based on the measurement of the similarity quality using fuzzy relations
title An improvement to the classification based on the measurement of the similarity quality using fuzzy relations
spellingShingle An improvement to the classification based on the measurement of the similarity quality using fuzzy relations
62 Ingeniería y operaciones afines / Engineering
classification rules
fuzzy sets
similarity relations
title_short An improvement to the classification based on the measurement of the similarity quality using fuzzy relations
title_full An improvement to the classification based on the measurement of the similarity quality using fuzzy relations
title_fullStr An improvement to the classification based on the measurement of the similarity quality using fuzzy relations
title_full_unstemmed An improvement to the classification based on the measurement of the similarity quality using fuzzy relations
title_sort An improvement to the classification based on the measurement of the similarity quality using fuzzy relations
dc.creator.fl_str_mv Fernandez Hernandez, Yumilka Barbara
Filiberto, Yaima
Frias, Mabel
Bello, Rafael
Caballero, Yaile
dc.contributor.author.spa.fl_str_mv Fernandez Hernandez, Yumilka Barbara
Filiberto, Yaima
Frias, Mabel
Bello, Rafael
Caballero, Yaile
dc.subject.ddc.spa.fl_str_mv 62 Ingeniería y operaciones afines / Engineering
topic 62 Ingeniería y operaciones afines / Engineering
classification rules
fuzzy sets
similarity relations
dc.subject.proposal.spa.fl_str_mv classification rules
fuzzy sets
similarity relations
description The learning of classification rules is a classic problem of the automatic learning. The algorithm IRBASIR for the induction of classification rules based on similaridad relations allows to discover knowledge starting from decision systems that contain features with continuous and discrete domains. This algorithm has shown to obtain higher results than other well-known algorithms. In this article, several modifications to this algorithm based on the Fuzzy sets theory are proposed, taking into account the measure quality of similarity. The experimental results show that using the fuzzy sets theory allow to obtain higher results than the original algorithm.
publishDate 2015
dc.date.issued.spa.fl_str_mv 2015-09-01
dc.date.accessioned.spa.fl_str_mv 2019-07-02T18:47:41Z
dc.date.available.spa.fl_str_mv 2019-07-02T18:47:41Z
dc.type.spa.fl_str_mv Artículo de revista
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dc.identifier.issn.spa.fl_str_mv ISSN: 2346-2183
dc.identifier.uri.none.fl_str_mv https://repositorio.unal.edu.co/handle/unal/60647
dc.identifier.eprints.spa.fl_str_mv http://bdigital.unal.edu.co/58979/
identifier_str_mv ISSN: 2346-2183
url https://repositorio.unal.edu.co/handle/unal/60647
http://bdigital.unal.edu.co/58979/
dc.language.iso.spa.fl_str_mv spa
language spa
dc.relation.spa.fl_str_mv https://revistas.unal.edu.co/index.php/dyna/article/view/45989
dc.relation.ispartof.spa.fl_str_mv Universidad Nacional de Colombia Revistas electrónicas UN Dyna
Dyna
dc.relation.references.spa.fl_str_mv Fernandez Hernandez, Yumilka Barbara and Filiberto, Yaima and Frias, Mabel and Bello, Rafael and Caballero, Yaile (2015) An improvement to the classification based on the measurement of the similarity quality using fuzzy relations. DYNA, 82 (193). pp. 70-76. ISSN 2346-2183
dc.rights.spa.fl_str_mv Derechos reservados - Universidad Nacional de Colombia
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.license.spa.fl_str_mv Atribución-NoComercial 4.0 Internacional
dc.rights.uri.spa.fl_str_mv http://creativecommons.org/licenses/by-nc/4.0/
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv Atribución-NoComercial 4.0 Internacional
Derechos reservados - Universidad Nacional de Colombia
http://creativecommons.org/licenses/by-nc/4.0/
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad Nacional de Colombia (Sede Medellín). Facultad de Minas.
institution Universidad Nacional de Colombia
bitstream.url.fl_str_mv https://repositorio.unal.edu.co/bitstream/unal/60647/1/45989-263859-2-PB.pdf
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