Evolution of Classification Rules for Comprehensible Knowledge Discovery

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  author =       "Emiliano Carreno and Guillermo Leguizamon and 
                 Neal Wagner",
  title =        "Evolution of Classification Rules for Comprehensible
                 Knowledge Discovery",
  booktitle =    "2007 IEEE Congress on Evolutionary Computation",
  year =         "2007",
  editor =       "Dipti Srinivasan and Lipo Wang",
  pages =        "1261--1268",
  address =      "Singapore",
  month =        "25-28 " # sep,
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  ISBN =         "1-4244-1340-0",
  file =         "1695.pdf",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CEC.2007.4424615",
  abstract =     "This article, which lies within the data mining
                 framework, proposes a method to build classifiers based
                 on the evolution of rules. The method, named REC (Rule
                 Evolution for Classifiers), has three main features: it
                 applies genetic programming to perform a search in the
                 space of potential solutions; a procedure allows
                 biasing the search towards regions of comprehensible
                 hypothesis with high predictive quality and it includes
                 a strategy for the selection of an optimum subset of
                 rules (classifier) from the rules obtained as the
                 result of the evolutionary process. A comparative study
                 between this method and the rule induction algorithm
                 C5.0 is carried out for two application problems (data
                 sets). Experimental results show the advantages of
                 using the method proposed.",
  notes =        "CEC 2007 - A joint meeting of the IEEE, the EPS, and
                 the IET.

                 IEEE Catalog Number: 07TH8963C",

Genetic Programming entries for Emiliano J Carreno Guillermo Leguizamon Neal Wagner