Applying interval type-2 fuzzy rule based classifiers through a cluster-based class representation

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Applying interval type-2 fuzzy rule based classifiers through a cluster-based class representation

Fuzzy Rule-Based Classification Systems (FRBCSs) have the potential to provide so-called interpretable classifiers, i.e. classifiers which can be introspective, understood, validated and augmented by human experts by relying on fuzzy-set based rules. This paper builds on prior work for interval type...

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Bibliographic Details
Main Authors:	Navarro, Javier, Wagner, Christian, Aickelin, Uwe
Format:	Conference or Workshop Item
Published:	2015
Online Access:	https://eprints.nottingham.ac.uk/33371/

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