Classifiers that approximate functions

@article{Wilson2004ClassifiersTA,
  title={Classifiers that approximate functions},
  author={S. Wilson},
  journal={Natural Computing},
  year={2004},
  volume={1},
  pages={211-234}
}
  • S. Wilson
  • Published 2004
  • Computer Science, Mathematics
  • Natural Computing
  • A classifier system, XCSF, is introduced in which the predictionestimation mechanism is used to learn approximations to functions.The addition of weight vectors to the classifiers allowspiecewise-linear approximation, where the classifier'sprediction is calculated instead of being a fixed scalar. The weight vector and the classifier's condition co-adapt.Results on functions of up to six dimensions show high accuracy. The idea of calculating the prediction leads to the concept ofa generalized… CONTINUE READING
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    References

    SHOWING 1-10 OF 28 REFERENCES
    Classifier Fitness Based on Accuracy
    • S. Wilson
    • Mathematics, Computer Science
    • Evolutionary Computation
    • 1995
    • 1,434
    • PDF
    An Analysis of Generalization in the XCS Classifier System
    • P. L. Lanzi
    • Mathematics, Computer Science
    • Evolutionary Computation
    • 1999
    • 332
    State of XCS Classifier System Research
    • S. Wilson
    • Computer Science
    • Learning Classifier Systems
    • 1999
    • 70
    • PDF
    XCS Classifier System Reliably Evolves Accurate, Complete, and Minimal Representations for Boolean Functions
    • 152
    • PDF
    Deletion schemes for classifier systems
    • 73
    Analyzing the evolutionary pressures in XCS
    • 61
    • PDF
    An Introduction to Learning Fuzzy Classifier Systems
    • 89
    Generalization in the XCS Classifier System
    • 266