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Quality versus quantity of rules in a classifier jury: extended abstract

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Published:06 July 2013Publication History

ABSTRACT

We show that under certain general circumstances there exists a choice of classifier rule length versus number of classifier rules, when given a fixed length classifier system, that maximizes performance of the system.

References

  1. D. Ashlock. Binary Series Prediction Contest, In WCCI 2006 and CEC 2006 competitions, http://eldar.mathstat.uoguelph.ca/dashlock/CEC05/BSP.html, 2006.Google ScholarGoogle Scholar
  2. D. E. Goldberg. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, New York, 1989. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Quality versus quantity of rules in a classifier jury: extended abstract

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      • Published in

        cover image ACM Conferences
        GECCO '13 Companion: Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
        July 2013
        1798 pages
        ISBN:9781450319645
        DOI:10.1145/2464576
        • Editor:
        • Christian Blum,
        • General Chair:
        • Enrique Alba

        Copyright © 2013 Copyright is held by the owner/author(s)

        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 6 July 2013

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