Obtaining a fuzzy classification rule system from a non-supervised clustering

Título:

Obtaining a fuzzy classification rule system from a non-supervised clustering

Autor:

Hasperué, Waldo

Colaboradores:

; Massa, G. O.; Lanzarini, Laura Cristina

Temas:

LÓGICA DIFUSAREDES NEURONALES

En:

International Conference on Information Technology Interfaces, 2008. ITI 2008 (30ª : 2008, Jun. 23-26 : Dubrovnik, Croacia), IEEE. 2008. pp.341-346

Resumen:

The fuzzy classification systems have been broadly used to solve control and decision- making problem. However, its design is complex, even when having a human expert assistance. This paper presents a new strategy capable of automatically defining the corresponding Fuzzy Classification Rule System from a non- supervised clustering of the available data. Its application to three data sets of the UCI repository has given quite satisfactory results.

URL/DOI:

http://dx.doi.org/10.1109/ITI.2008.4588433

Medio:

Soporte electrónico

Tipo de documento:

Artículo

Descripción física:

1 archivo (126,5 kB)

Idioma:

Inglés

Publicación:

IEEE Press, 2008

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