Applying genetic programming technique in classification trees

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

  author =       "Chan-Sheng Kuo and Tzung-Pei Hong and 
                 Chuen-Lung Chen",
  title =        "Applying genetic programming technique in
                 classification trees",
  journal =      "Soft Computing",
  year =         "2007",
  volume =       "11",
  number =       "12",
  pages =        "1165--1172",
  month =        oct,
  keywords =     "genetic algorithms, genetic programming,
                 Classification tree, Knowledge base, Genetic operator",
  ISSN =         "1432-7643",
  DOI =          "doi:10.1007/s00500-007-0159-x",
  size =         "8 pages",
  abstract =     "Classification problems are often encountered in many
                 applications. In the past, classification trees were
                 often generated by decision-tree methods and commonly
                 used to solve classification problems. In this paper,
                 we have proposed an algorithm based on genetic
                 programming to search for an appropriate classification
                 tree according to some criteria. The classification
                 tree obtained can be transferred into a rule set, which
                 can then be fed into a knowledge base to support
                 decision making and facilitate daily operations. Two
                 new genetic operators, elimination and merge, are
                 designed in the proposed approach to remove redundancy
                 and subsumption, thus producing more accurate and
                 concise decision rules than that without using them.
                 Experimental results from the credit card data also
                 show the feasibility of the proposed algorithm.",
  bibdate =      "2008-03-11",
  bibsource =    "DBLP,

Genetic Programming entries for Chan-Sheng Kuo Tzung-Pei Hong Samuel Chuen-Lung Chen