Adaptive decision making systems
- Autores
- Bulacio, Pilar; Magdalena, Luis; Tapia, Elizabeth
- Año de publicación
- 2005
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- Given a population of classifiers, we consider the problem of designing highly compact and error adaptive decision making systems. A selection approach based on misclassification diversity and potential cooperation among classifiers is proposed. The compactness constraint allows us the efficient implementation of fuzzy integral combination rules regarding both the interpretability of fuzzy measures and low complexity of fuzzy integral operator. Experimental results show the feasibility of our approach.
VI Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI) - Materia
-
Ciencias Informáticas
scalability
multiclassifier system
fuzzy integral
Logic Programming - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/22982
Ver los metadatos del registro completo
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Adaptive decision making systemsBulacio, PilarMagdalena, LuisTapia, ElizabethCiencias Informáticasscalabilitymulticlassifier systemfuzzy integralLogic ProgrammingGiven a population of classifiers, we consider the problem of designing highly compact and error adaptive decision making systems. A selection approach based on misclassification diversity and potential cooperation among classifiers is proposed. The compactness constraint allows us the efficient implementation of fuzzy integral combination rules regarding both the interpretability of fuzzy measures and low complexity of fuzzy integral operator. Experimental results show the feasibility of our approach.VI Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI)2005-10info: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/10915/22982enginfo: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:UNLP2025-09-29T10:55:16Zoai:sedici.unlp.edu.ar:10915/22982Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:55:16.978SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Adaptive decision making systems |
title |
Adaptive decision making systems |
spellingShingle |
Adaptive decision making systems Bulacio, Pilar Ciencias Informáticas scalability multiclassifier system fuzzy integral Logic Programming |
title_short |
Adaptive decision making systems |
title_full |
Adaptive decision making systems |
title_fullStr |
Adaptive decision making systems |
title_full_unstemmed |
Adaptive decision making systems |
title_sort |
Adaptive decision making systems |
dc.creator.none.fl_str_mv |
Bulacio, Pilar Magdalena, Luis Tapia, Elizabeth |
author |
Bulacio, Pilar |
author_facet |
Bulacio, Pilar Magdalena, Luis Tapia, Elizabeth |
author_role |
author |
author2 |
Magdalena, Luis Tapia, Elizabeth |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas scalability multiclassifier system fuzzy integral Logic Programming |
topic |
Ciencias Informáticas scalability multiclassifier system fuzzy integral Logic Programming |
dc.description.none.fl_txt_mv |
Given a population of classifiers, we consider the problem of designing highly compact and error adaptive decision making systems. A selection approach based on misclassification diversity and potential cooperation among classifiers is proposed. The compactness constraint allows us the efficient implementation of fuzzy integral combination rules regarding both the interpretability of fuzzy measures and low complexity of fuzzy integral operator. Experimental results show the feasibility of our approach. VI Workshop de Agentes y Sistemas Inteligentes (WASI) Red de Universidades con Carreras en Informática (RedUNCI) |
description |
Given a population of classifiers, we consider the problem of designing highly compact and error adaptive decision making systems. A selection approach based on misclassification diversity and potential cooperation among classifiers is proposed. The compactness constraint allows us the efficient implementation of fuzzy integral combination rules regarding both the interpretability of fuzzy measures and low complexity of fuzzy integral operator. Experimental results show the feasibility of our approach. |
publishDate |
2005 |
dc.date.none.fl_str_mv |
2005-10 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/22982 |
url |
http://sedici.unlp.edu.ar/handle/10915/22982 |
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:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
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SEDICI (UNLP) |
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SEDICI (UNLP) |
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Universidad Nacional de La Plata |
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UNLP |
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SEDICI (UNLP) - Universidad Nacional de La Plata |
repository.mail.fl_str_mv |
alira@sedici.unlp.edu.ar |
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score |
13.070432 |