Searching the Forest: Using Decision Trees as Building Blocks for Evolutionary Search in Classification Databases

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{engelbrecht:2000:SFUDTBBESCD,
  author =       "S. E. Rouwhorst and A. P. Engelbrecht",
  title =        "Searching the Forest: Using Decision Trees as Building
                 Blocks for Evolutionary Search in Classification
                 Databases",
  booktitle =    "Proceedings of the 2000 Congress on Evolutionary
                 Computation CEC00",
  year =         "2000",
  pages =        "633--638",
  volume =       "1",
  address =      "La Jolla Marriott Hotel La Jolla, California, USA",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  month =        "6-9 " # jul,
  organisation = "IEEE Neural Network Council (NNC), Evolutionary
                 Programming Society (EPS), Institution of Electrical
                 Engineers (IEE)",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, hybrid
                 systems, data mining, decision trees, evolutionary
                 computation, mathematical operators, pattern
                 classification, search problems, BGP algorithm, C4.5
                 algorithm, CN2 algorithm, building blocks,
                 classification databases, data mining, decision trees,
                 evolutionary search algorithm, induction algorithms,
                 operators",
  ISBN =         "0-7803-6375-2",
  DOI =          "doi:10.1109/CEC.2000.870357",
  size =         "6 pages",
  abstract =     "A new evolutionary search algorithm, called BGP
                 (Building-block approach to Genetic Programming), to be
                 used for classification tasks in data mining, is
                 introduced. It is different from existing evolutionary
                 techniques in that it does not use indirect
                 representations of a solution, such as bit strings or
                 grammars. The algorithm uses decision trees of various
                 sizes as individuals in the populations and operators,
                 e.g. crossover, are performed directly on the trees.
                 When compared to the C4.5 and CN2 induction algorithms
                 on a benchmark set of problems, BGP shows very good
                 results",
  notes =        "CEC-2000 - A joint meeting of the IEEE, Evolutionary
                 Programming Society, Galesia, and the IEE.

                 IEEE Catalog Number = 00TH8512,

                 Library of Congress Number = 00-018644

                 Inspec Accession Number: 6734684

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

Genetic Programming entries for Sonja E Rouwhorst Andries P Engelbrecht

Citations