Discovering Fuzzy Classification Rules with Genetic Programming and Co-Evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Roberto R. F. Mendes and Fabricio B. Voznika and 
                 Alex A. Freitas and Julio C. Nievola",
  title =        "Discovering Fuzzy Classification Rules with Genetic
                 Programming and Co-Evolution",
  booktitle =    "5th European Conference on Principles and Practice of
                 Knowledge Discovery in Databases (PKDD'01)",
  year =         "2001",
  editor =       "L. {de Raedt} and Arno Siebes",
  volume =       "2168",
  series =       "LNAI",
  pages =        "314--325",
  address =      "Freiburg, Germany",
  month =        "3-7 " # sep,
  publisher =    "Springer Verlag",
  keywords =     "genetic algorithms, genetic programming, data mining,
                 classification, co-evolution",
  URL =          "",
  URL =          "",
  URL =          "",
  size =         "12 pages",
  abstract =     "In essence, data mining consists of extracting
                 knowledge from data. This paper proposes a
                 co-evolutionary system for discovering fuzzy
                 classification rules. The system uses two evolutionary
                 algorithms: a genetic programming (GP) algorithm
                 evolving a population of fuzzy rule sets and a simple
                 evolutionary algorithm evolving a population of of
                 membership function definitions. The two populations
                 co-evolve, so that the final result of the
                 co-evolutionary process is a fuzzy rule set and a set
                 of membership function definitions which are well
                 adapted to each other. In addition, our system also has
                 some innovative ideas with respect to the encoding of
                 GP individuals representing rule sets. The basic idea
                 is that our individual encoding scheme incorporates
                 several syntactical restrictions that facilitate the
                 handling of rule sets in disjunctive normal form. We
                 have also adapted GP operators to better work with the
                 proposed individual encoding scheme.",
  notes =        "

                 Comparison in \cite{yu:2004:ECDM}",

Genetic Programming entries for Roberto R F Mendes Fabricio de B Voznika Alex Alves Freitas Julio C Nievola