Evolving Fuzzy Decision Trees with Genetic Programming and Clustering

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

  title =        "Evolving Fuzzy Decision Trees with Genetic Programming
                 and Clustering",
  author =       "Jeroen Eggermont",
  editor =       "James A. Foster and Evelyne Lutton and 
                 Julian Miller and Conor Ryan and Andrea G. B. Tettamanzi",
  booktitle =    "Genetic Programming, Proceedings of the 5th European
                 Conference, EuroGP 2002",
  volume =       "2278",
  series =       "LNCS",
  pages =        "71--82",
  publisher =    "Springer-Verlag",
  address =      "Kinsale, Ireland",
  publisher_address = "Berlin",
  month =        "3-5 " # apr,
  year =         "2002",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-43378-3",
  URL =          "http://www.liacs.nl/~jeggermo/publications/eurogp2002.ps.gz",
  DOI =          "doi:10.1007/3-540-45984-7_7",
  abstract =     "In this paper we present a new fuzzy decision tree
                 representation for n-category data classification using
                 genetic programming. The new fuzzy representation uses
                 fuzzy clusters for handling continuous attributes. To
                 make optimal use of the fuzzy classifications of this
                 representation an extra fitness measure is used. The
                 new fuzzy representation will be compared, using
                 several machine learning data sets, to a similar
                 non-fuzzy representation as well as to some other
                 evolutionary and non-evolutionary algorithms from
  notes =        "EuroGP'2002, part of \cite{lutton:2002:GP}",

Genetic Programming entries for Jeroen Eggermont