Learning hybrid neuro-fuzzy classifier models from data: to combine or not to combine?

DOI10.1016/j.fss.2003.11.010zbMath1067.68596OpenAlexW2034692175MaRDI QIDQ1885675

Bogdan Gabrys

Publication date: 12 November 2004

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

Full work available at URL: http://eprints.bournemouth.ac.uk/8539/1/Gabrys_EUNITE2001.pdf

zbMATH Keywords

Pattern recognitionCross-validationNeuro-fuzzy classifierClassifier combinationResampling techniquesEnsembles of classifiers

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (3)

Neuro-fuzzy approach to processing inputs with missing values in pattern recognition problems. ⋮ AutonoML: Towards an Integrated Framework for Autonomous Machine Learning ⋮ Automated adaptation strategies for stream learning

Cites Work

• Bagging predictors
• Neuro-fuzzy approach to processing inputs with missing values in pattern recognition problems.
• Agglomerative learning algorithms for general fuzzy Min-Max neural network
• Fuzzy classifier design
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