Applying interval type-2 fuzzy rule based classifiers through a cluster-based class representation
(2015)
Presentation / Conference Contribution
Navarro, J., Wagner, C., & Aickelin, U. (2015). 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.... Read More about Applying interval type-2 fuzzy rule based classifiers through a cluster-based class representation.