Discovering interesting classification rules with genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  author =       "I. {De Falco} and A. {Della Cioppa} and E. Tarantino",
  title =        "Discovering interesting classification rules with
                 genetic programming",
  journal =      "Applied Soft Computing",
  year =         "2001",
  volume =       "1",
  number =       "4",
  pages =        "257--269",
  month =        may,
  keywords =     "genetic algorithms, genetic programming, Data mining,
  URL =          "",
  URL =          "",
  DOI =          "doi:10.1016/S1568-4946(01)00024-2",
  abstract =     "Data mining deals with the problem of discovering
                 novel and interesting knowledge from large amount of
                 data. This problem is often performed heuristically
                 when the extraction of patterns is difficult using
                 standard query mechanisms or classical statistical
                 methods. In this paper a genetic programming framework,
                 capable of performing an automatic discovery of
                 classification rules easily comprehensible by humans,
                 is presented. A comparison with the results achieved by
                 other techniques on a classical benchmark set is
                 carried out. Furthermore, some of the obtained rules
                 are shown and the most discriminating variables are
  notes =        "comparsison in \cite{yu:2004:ECDM}",

Genetic Programming entries for Ivanoe De Falco Antonio Della Cioppa Ernesto Tarantino