A parsimonious generation of combinatorial neural model

This paper presents a new approach to reduce the space problem due to combinatorial explosion of CNM (Combinatorial Neural Model) method. First we show a description of CNM, proposed by Machado and Rocha [MAC 91], [MAC 92], [MAC 92a], [MAC 97], as a variation of fuzzy neural network introduced as an...

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Detalles Bibliográficos
Autores principales:	Prado, Hércules A., Frigeri, Sandra, Engel, Paulo Martins
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	1998
Materias:	Ciencias Informáticas Informática Neural nets Learning Data mining data minning knowledge discovery from databases supervised learning hybrid systems neural networks
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/24829
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-24829
record_format	dspace
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Ciencias Informáticas Informática Neural nets Learning Data mining data minning knowledge discovery from databases supervised learning hybrid systems neural networks
spellingShingle	Ciencias Informáticas Informática Neural nets Learning Data mining data minning knowledge discovery from databases supervised learning hybrid systems neural networks Prado, Hércules A. Frigeri, Sandra Engel, Paulo Martins A parsimonious generation of combinatorial neural model
topic_facet	Ciencias Informáticas Informática Neural nets Learning Data mining data minning knowledge discovery from databases supervised learning hybrid systems neural networks
description	This paper presents a new approach to reduce the space problem due to combinatorial explosion of CNM (Combinatorial Neural Model) method. First we show a description of CNM, proposed by Machado and Rocha [MAC 91], [MAC 92], [MAC 92a], [MAC 97], as a variation of fuzzy neural network introduced as an alternative to meet many requirements, such as expressiveness, inteligibility, plasticity and flexibility. Our approach represents an alternative to generate the CNM network with certainty factors for each hypothesis. We demonstrate by means of a simple practical example that the number of combinations can be really reduced.
format	Objeto de conferencia Objeto de conferencia
author	Prado, Hércules A. Frigeri, Sandra Engel, Paulo Martins
author_facet	Prado, Hércules A. Frigeri, Sandra Engel, Paulo Martins
author_sort	Prado, Hércules A.
title	A parsimonious generation of combinatorial neural model
title_short	A parsimonious generation of combinatorial neural model
title_full	A parsimonious generation of combinatorial neural model
title_fullStr	A parsimonious generation of combinatorial neural model
title_full_unstemmed	A parsimonious generation of combinatorial neural model
title_sort	parsimonious generation of combinatorial neural model
publishDate	1998
url	http://sedici.unlp.edu.ar/handle/10915/24829
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A parsimonious generation of combinatorial neural model

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