Solving multi-class problems with linguistic fuzzy rule based classification systems based on pairwise learning and preference relations

DOI10.1016/J.FSS.2010.05.016zbMath1209.68412OpenAlexW2164832081WikidataQ57865972 ScholiaQ57865972MaRDI QIDQ622072

Francisco Herrera, Alberto Fernández, María Calderón, Edurne Barrenechea, Humberto Bustince

Publication date: 31 January 2011

Published in: Fuzzy Sets and Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.fss.2010.05.016

zbMATH Keywords

fuzzy rule-based classification systemspairwise learningfuzzy preference relationsmulti-class problemsmulti-classifiers

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (6)

Enhancing evolutionary fuzzy systems for multi-class problems: distance-based relative competence weighting with truncated confidences (DRCW-TC) ⋮ Empowering difficult classes with a similarity-based aggregation in multi-class classification problems ⋮ A new interval type-2 fuzzy reasoning method for classification systems based on normal forms of a possibility-based fuzzy measure ⋮ A parsimony fuzzy rule-based classifier using axiomatic fuzzy set theory and support vector machines ⋮ Generalization of the weighted voting method using penalty functions constructed via faithful restricted dissimilarity functions ⋮ A fuzzy linear programming method for group decision making with additive reciprocal fuzzy preference relations

Uses Software

• UCI-ml
• KEEL

Cites Work

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• Combining predictions in pairwise classification: an optimal adaptive voting strategy and its relation to weighted voting
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• Decision-making with a fuzzy preference relation
• Ten years of genetic fuzzy systems: Current framework and new trends.
• Classification by pairwise coupling
• 10.1162/15324430152733133
• Classification and Modeling with Linguistic Information Granules
• 10.1162/153244302320884605

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