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Título:
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Relevance and Recundancy in fuzzy classification systems.
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Autores:
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Amo, Ana del ;
Gomez, D. ;
Montero, Javier ;
Biging, G.
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Tipo de documento:
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texto impreso
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Editorial:
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European Society for Fuzzy Logic and Technology, 2001
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Dimensiones:
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application/pdf
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Nota general:
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info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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Idiomas:
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,
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Palabras clave:
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Estado = Publicado
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Materia = Ciencias: Matemáticas: Investigación operativa
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Tipo = Artículo
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Resumen:
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Fuzzy classification systems is defined in this paper as an aggregative model, in such a way that Ruspini classical definition of fuzzy partition appears as a particular case. Once a basic recursive model has been accepted, we then propose to analyze relevance and redundancy in order to allow the possibility of learning from previous experiences. All these concepts are applied to a real picture, showing that our approach allows to check quality of such a classification system.
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En línea:
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https://eprints.ucm.es/id/eprint/29668/6/Montero129%201.pdf
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