Fuzzy rule selection by multi-objective genetic local search algorithms and rule evaluation measures in data mining.

DOI10.1016/S0165-0114(03)00114-3zbMath1081.68091OpenAlexW2109518982MaRDI QIDQ1430852

Takashi Yamamoto, Hisao Ishibuchi

Publication date: 27 May 2004

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

Full work available at URL: https://doi.org/10.1016/s0165-0114(03)00114-3

zbMATH Keywords

Data miningPattern classificationEvolutionary multi-criteria optimizationFuzzy rule selectionHybrid genetic algorithms

Mathematics Subject Classification ID

Database theory (68P15) Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

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Uses Software

• C4.5

Cites Work

• Three-objective genetics-based machine learning for linguistic rule extraction
• Including a simplicity criterion in the selection of the best rule in a genetic fuzzy learning algorithm
• Use of a fuzzy machine learning technique in the knowledge acquisition process
• Fuzzy classifier design
• Genetic local search for multi-objective combinatorial optimization
• Unnamed Item

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