A four-parameter beta distribution membership function lets a learning classifier system adapt each rule's boundary shape and fuzziness, improving test accuracy and rule compactness on 25 classification benchmarks.
Can the same rule representation change its matching area? enhancing representation in XCS for continuous space by probability distribution in multiple dimension,
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Adapting Rule Representation With Four-Parameter Beta Distribution for Learning Classifier Systems
A four-parameter beta distribution membership function lets a learning classifier system adapt each rule's boundary shape and fuzziness, improving test accuracy and rule compactness on 25 classification benchmarks.