Assessing different rule quality measures in a genetic algorithm for discovering association rules

Autores
Soto, Wilson; Olaya Benavides, Amparo
Año de publicación
2012
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The genetic algorithms have seen applied in knowledge discovery and specially for discovering association rules. In this paper, we explore the use of di erent rule quality measures in the tness function in a genetic algorithm for discovering association rules. Also, we present an improvement for this algorithm: (i) the mutation stage is calculated with a probability independent for each individual and (ii) the selection stage is calculated with Boltzmann selection. The proposed version was tested with 10 di erent rule quality evaluation functions on 6 benchmark datasets.
Eje: Workshop Bases de datos y minería de datos (WBDDM)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Algorithms
base de datos
Data mining
Knowledge Discovery
Association Rules
Genetic Algorithm
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/23749
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/23749
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Assessing different rule quality measures in a genetic algorithm for discovering association rulesSoto, WilsonOlaya Benavides, AmparoCiencias InformáticasAlgorithmsbase de datosData miningKnowledge DiscoveryAssociation RulesGenetic AlgorithmThe genetic algorithms have seen applied in knowledge discovery and specially for discovering association rules. In this paper, we explore the use of di erent rule quality measures in the tness function in a genetic algorithm for discovering association rules. Also, we present an improvement for this algorithm: (i) the mutation stage is calculated with a probability independent for each individual and (ii) the selection stage is calculated with Boltzmann selection. The proposed version was tested with 10 di erent rule quality evaluation functions on 6 benchmark datasets.Eje: Workshop Bases de datos y minería de datos (WBDDM)Red de Universidades con Carreras en Informática (RedUNCI)2012-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/23749enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:55:35Zoai:sedici.unlp.edu.ar:10915/23749Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:55:35.808SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Assessing different rule quality measures in a genetic algorithm for discovering association rules
title Assessing different rule quality measures in a genetic algorithm for discovering association rules
spellingShingle Assessing different rule quality measures in a genetic algorithm for discovering association rules
Soto, Wilson
Ciencias Informáticas
Algorithms
base de datos
Data mining
Knowledge Discovery
Association Rules
Genetic Algorithm
title_short Assessing different rule quality measures in a genetic algorithm for discovering association rules
title_full Assessing different rule quality measures in a genetic algorithm for discovering association rules
title_fullStr Assessing different rule quality measures in a genetic algorithm for discovering association rules
title_full_unstemmed Assessing different rule quality measures in a genetic algorithm for discovering association rules
title_sort Assessing different rule quality measures in a genetic algorithm for discovering association rules
dc.creator.none.fl_str_mv Soto, Wilson
Olaya Benavides, Amparo
author Soto, Wilson
author_facet Soto, Wilson
Olaya Benavides, Amparo
author_role author
author2 Olaya Benavides, Amparo
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Algorithms
base de datos
Data mining
Knowledge Discovery
Association Rules
Genetic Algorithm
topic Ciencias Informáticas
Algorithms
base de datos
Data mining
Knowledge Discovery
Association Rules
Genetic Algorithm
dc.description.none.fl_txt_mv The genetic algorithms have seen applied in knowledge discovery and specially for discovering association rules. In this paper, we explore the use of di erent rule quality measures in the tness function in a genetic algorithm for discovering association rules. Also, we present an improvement for this algorithm: (i) the mutation stage is calculated with a probability independent for each individual and (ii) the selection stage is calculated with Boltzmann selection. The proposed version was tested with 10 di erent rule quality evaluation functions on 6 benchmark datasets.
Eje: Workshop Bases de datos y minería de datos (WBDDM)
Red de Universidades con Carreras en Informática (RedUNCI)
description The genetic algorithms have seen applied in knowledge discovery and specially for discovering association rules. In this paper, we explore the use of di erent rule quality measures in the tness function in a genetic algorithm for discovering association rules. Also, we present an improvement for this algorithm: (i) the mutation stage is calculated with a probability independent for each individual and (ii) the selection stage is calculated with Boltzmann selection. The proposed version was tested with 10 di erent rule quality evaluation functions on 6 benchmark datasets.
publishDate 2012
dc.date.none.fl_str_mv 2012-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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http://purl.org/coar/resource_type/c_5794
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status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/23749
url http://sedici.unlp.edu.ar/handle/10915/23749
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
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reponame_str SEDICI (UNLP)
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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