Genetic Programming for Data Classification: Partitioning the Search Space

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{eggermont:2004:sac,
  author =       "Jeroen Eggermont and Joost N. Kok and 
                 Walter A. Kosters",
  title =        "Genetic Programming for Data Classification:
                 Partitioning the Search Space",
  booktitle =    "Proceedings of the 2004 Symposium on applied computing
                 (ACM SAC'04)",
  year =         "2004",
  pages =        "1001--1005",
  address =      "Nicosia, Cyprus",
  month =        "14-17 " # mar,
  keywords =     "genetic algorithms, genetic programming, data
                 classification",
  URL =          "http://www.liacs.nl/~kosters/SAC2003final.pdf",
  DOI =          "doi:10.1145/967900.968104",
  size =         "5 pages",
  abstract =     "When Genetic Programming is used to evolve decision
                 trees for data classification, search spaces tend to
                 become extremely large. We present several methods
                 using techniques from the field of machine learning to
                 refine and thereby reduce the search space sizes for
                 decision tree evolvers. We will show that these
                 refinement methods improve the classification
                 performance of our algorithms.",
}

Genetic Programming entries for Jeroen Eggermont Joost Kok Walter A Kosters

Citations