Intelligent classification through exclusion/inclusion relationship

Bargiela, A. and Pedrycz, W., 2003. Intelligent classification through exclusion/inclusion relationship. In: AI-METH 2003, Symposium on Methods of Artificial Intelligence, Gliwice, Poland, 5-7 November 2003. Gliwice, Poland: Silesian University of Technology, pp. 17-20. ISBN 8391463273

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Abstract

The paper introduces an exclusion/inclusion fuzzy classification (EFC) neural network. The network is based on our general fuzzy min-max algorithm (GFMM [13]) and it allows for two distinct types of hyperboxes to be created: inclusion hyperboxes, that corresponds directly to those considered in GFMM, and exclusion hyperboxes that represent contentious areas of the patter space. The subtraction of the exclusion hyperboxes from the inclusion hyperboxes, implemented by EFC, provides for a more efficient coverage of complex topologies of data clusters

Item Type:	Chapter in book
Creators:	Bargiela, A. and Pedrycz, W.
Publisher:	Silesian University of Technology
Place of Publication:	Gliwice, Poland
Date:	2003
ISBN:	8391463273
Divisions:	Schools > School of Science and Technology
Record created by:	EPrints Services
Date Added:	09 Oct 2015 10:39
Last Modified:	19 Oct 2015 14:35
URI:	https://irep.ntu.ac.uk/id/eprint/16063

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