Ensemble techniques for Parallel Genetic Programming based Classifiers

Created by W.Langdon from gp-bibliography.bib Revision:1.4333

  author =       "Gianluigi Folino and Clara Pizzuti and 
                 Giandomenico Spezzano",
  title =        "Ensemble techniques for Parallel Genetic Programming
                 based Classifiers",
  booktitle =    "Genetic Programming, Proceedings of EuroGP'2003",
  year =         "2003",
  editor =       "Conor Ryan and Terence Soule and Maarten Keijzer and 
                 Edward Tsang and Riccardo Poli and Ernesto Costa",
  volume =       "2610",
  series =       "LNCS",
  pages =        "59--69",
  address =      "Essex",
  publisher_address = "Berlin",
  month =        "14-16 " # apr,
  organisation = "EvoNet",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-00971-X",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2610&spage=59",
  DOI =          "doi:10.1007/3-540-36599-0_6",
  abstract =     "An extension of Cellular Genetic Programming for data
                 classification to induce an ensemble of predictors is
                 presented. Each classifier is trained on a different
                 subset of the overall data, then they are combined to
                 classify new tuples by applying a simple majority
                 voting algorithm, like bagging. Preliminary results on
                 a large data set show that the ensemble of classifiers
                 trained on a sample of the data obtains higher accuracy
                 than a single classifier that uses the entire data set
                 at a much lower computational cost.",
  notes =        "EuroGP'2003 held in conjunction with EvoWorkshops

Genetic Programming entries for Gianluigi Folino Clara Pizzuti Giandomenico Spezzano