Including a simplicity criterion in the selection of the best rule in a genetic fuzzy learning algorithm

DOI10.1016/S0165-0114(99)00095-0zbMath1013.68178OpenAlexW2164159077MaRDI QIDQ5937031

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Publication date: 12 July 2001

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

Full work available at URL: https://doi.org/10.1016/s0165-0114(99)00095-0

zbMATH Keywords

learning algorithmsgenetic fuzzy learning algorithm

Mathematics Subject Classification ID

Nonnumerical algorithms (68W05) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (6)

A feature construction approach for genetic iterative rule learning algorithm ⋮ An interpretability improvement for fuzzy rule bases obtained by the iterative rule learning approach ⋮ Ten years of genetic fuzzy systems: Current framework and new trends. ⋮ Fuzzy rule selection by multi-objective genetic local search algorithms and rule evaluation measures in data mining. ⋮ MIXED GENETIC ALGORITHM APPROACH FOR FUZZY CLASSIFIER DESIGN ⋮ FuzzyFeatureRank. Bringing order into fuzzy classifiers through fuzzy expressions

Uses Software

• UCI-ml
• Genocop
• C4.5

Cites Work

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• A fuzzy logic controller with learning through the evolution of its knowledge base
• Adapting the gain of an FLC with genetic algorithms
• A three-stage evolutionary process for learning descriptive and approximate fuzzy-logic-controller knowledge bases from examples.
• The concept of a linguistic variable and its application to approximate reasoning. I
• A genetic algorithm for generating fuzzy classification rules
• A learning methodology in uncertain and imprecise environments

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