Details

Autor(en) / Beteiligte

• Casillas, J.
• Orriols-Puig, A.
• Bernado-Mansilla, E.

Titel

Toward evolving consistent, complete, and compact fuzzy rule sets for classification problems

Ist Teil von

• 2008 3rd International Workshop on Genetic and Evolving Systems, 2008, p.89-94

Ort / Verlag

IEEE

Erscheinungsjahr

2008

Quelle

IEEE/IET Electronic Library

Beschreibungen/Notizen

• This paper proposes Pitts-DNF-C, a multi- objective Pittsburgh-style Learning Classifier System that evolves a set of DNF-type fuzzy rules for classification tasks. The system is explicitly designed to only explore solutions that lead to consistent, complete, and compact rule sets without redundancies and inconsistencies. The behavior of the system is analyzed on a collection of real-world data sets, showing its competitiveness in terms of performance and interpretability with respect to three other fuzzy learners.