Inference in classifier systems

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dc.contributor.author Muruzábal, Jorge
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned 2009-02-20T12:04:03Z
dc.date.available 2009-02-20T12:04:03Z
dc.date.issued 1993-09
dc.identifier.uri http://hdl.handle.net/10016/3730
dc.description.abstract Classifier systems (Css) provide a rich framework for learning and induction, and they have beenı successfully applied in the artificial intelligence literature for some time. In this paper, both theı architecture and the inferential mechanisms in general CSs are reviewed, and a number of limitations and extensions of the basic approach are summarized. A system based on the CS approach that is capable of quantitative data analysis is outlined and some of its peculiarities discussed.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working Papers. Statistics and Econometrics
dc.relation.ispartofseries 1993-18-14
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Classifier systems
dc.subject.other Machine learning
dc.subject.other Exploratory data analysis
dc.title Inference in classifier systems
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
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