A Study on Efficient Generation of Decision Trees Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Toru Tanigawa and Qiangfu Zhao",
  title =        "A Study on Efficient Generation of Decision Trees
                 Using Genetic Programming",
  pages =        "1047--1052",
  year =         "2000",
  publisher =    "Morgan Kaufmann",
  booktitle =    "Proceedings of the Genetic and Evolutionary
                 Computation Conference (GECCO-2000)",
  editor =       "Darrell Whitley and David Goldberg and 
                 Erick Cantu-Paz and Lee Spector and Ian Parmee and Hans-Georg Beyer",
  address =      "Las Vegas, Nevada, USA",
  publisher_address = "San Francisco, CA 94104, USA",
  month =        "10-12 " # jul,
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "1-55860-708-0",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2000/NN260.pdf",
  URL =          "http://www.u-aizu.ac.jp/~qf-zhao/CONTRIBUTION/gecco2000.ps.Z",
  URL =          "http://citeseer.ist.psu.edu/498621.html",
  size =         "6 pages",
  abstract =     "For pattern recognition, the decision trees (DTs) are
                 more efficient than neural networks (NNs) for two
                 reasons. First, the computations in making decisions
                 are simpler. Second, important features can be selected
                 automatically during the design process. On the other
                 hand, NNs are adaptable, and thus have the ability to
                 learn in changing environment.",
  notes =        "A joint meeting of the ninth International Conference
                 on Genetic Algorithms (ICGA-2000) and the fifth Annual
                 Genetic Programming Conference (GP-2000) Part of

Genetic Programming entries for Toru Tanigawa Qiangfu Zhao