An Innovative Approach to Genetic Programming-based Clustering

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

  author =       "I. {De Falco} and E. Tarantino and 
                 A. {Della Cioppa} and F. Fontanella",
  title =        "An Innovative Approach to Genetic Programming-based
  booktitle =    "9th Online World Conference on Soft Computing in
                 Industrial Applications",
  year =         "2004",
  editor =       "Ajith Abraham and Bernard {de Baets} and 
                 Mario Koeppen and Bertram Nickolay",
  volume =       "34",
  series =       "Advances in Soft Computing",
  pages =        "55--64",
  address =      "On the World Wide Web",
  month =        "20 " # sep # " - 8 " # oct,
  organisation = "World Federation on Soft Computing (WFSC)",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming, clustering",
  isbn13 =       "978-3-540-31649-7",
  URL =          "",
  DOI =          "doi:10.1007/3-540-31662-0_4",
  size =         "10 pages",
  abstract =     "Most of the classical clustering algorithms are
                 strongly dependent on, and sensitive to, parameters
                 such as number of expected clusters and resolution
                 level. To overcome this drawback, in this paper a
                 Genetic Programming framework, capable of performing an
                 automatic data clustering is presented. Moreover, a
                 novel way of representing clusters which provides
                 intelligible information on patterns is introduced
                 together with an innovative clustering process. The
                 effectiveness of the implemented partitioning system is
                 estimated on a medical domain by means of evaluation
  notes =        "WSC9

                 Clusters represented using GP evolved functions.
                 Grammar. Fitness is linear combination of cluster
                 homogeneity and separation. Non standard crossover.
                 Multiple classes. UCI dermatological benchmark.",

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