A parsimony fuzzy rule-based classifier using axiomatic fuzzy set theory and support vector machines

DOI10.1016/j.ins.2011.07.027zbMath1239.68063OpenAlexW1968447469WikidataQ60248792 ScholiaQ60248792MaRDI QIDQ424770

Jiannong Cao, Yan Ren, Xiao Dong Liu

Publication date: 4 June 2012

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2011.07.027

zbMATH Keywords

outliersinterpretabilitysupport vector machinesAFS algebrasfuzzy descriptions

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (2)

A hybrid-forecasting model reducing Gaussian noise based on the Gaussian support vector regression machine and chaotic particle swarm optimization ⋮ An integer programming approach for fuzzy rule-based classification systems

Uses Software

• UCI-ml
• LIBSVM
• C4.5

Cites Work

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• Solving multi-class problems with linguistic fuzzy rule based classification systems based on pairwise learning and preference relations
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• Induction of multiple fuzzy decision trees based on rough set technique
• Axiomatic fuzzy set theory and its applications
• The framework of axiomatics fuzzy sets based fuzzy classifiers
• The fuzzy sets and systems based on AFS. structure, EI algebra and EII algebra
• The fuzzy theory based on AFS algebras and AFS structure
• Interpretability issues in fuzzy modeling
• Support-vector networks
• Learning fuzzy rules from fuzzy samples based on rough set technique
• Extraction of fuzzy rules from support vector machines
• Outline of a New Approach to the Analysis of Complex Systems and Decision Processes

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