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dc.date.accessioned 2012-10-26T11:29:21Z
dc.date.available 2012-10-26T11:29:21Z
dc.date.issued 2005-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/22982
dc.description.abstract 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. en
dc.language en es
dc.subject scalability en
dc.subject Logic Programming es
dc.subject multiclassifier system en
dc.subject fuzzy integral en
dc.title Adaptive decision making systems en
dc.type Objeto de conferencia es
sedici.creator.person Bulacio, Pilar es
sedici.creator.person Magdalena, Luis es
sedici.creator.person Tapia, Elizabeth es
sedici.description.note VI Workshop de Agentes y Sistemas Inteligentes (WASI) es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2005-10
sedici.relation.event XI Congreso Argentino de Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Except where otherwise noted, this item's license is described as Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)