Anti-correlation: A Diversity Promoting Mechanisms in Ensemble Learning

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{McKay:2001:AJIIPS_2,
  author =       "R. I. (Bob) McKay and Hussein A. Abbass",
  journal =      "The Australian Journal of Intelligent Information
                 Processing Systems",
  number =       "3/4",
  pages =        "139--149",
  title =        "Anti-correlation: A Diversity Promoting Mechanisms in
                 Ensemble Learning",
  URL =          "http://sc.snu.ac.kr/PAPERS/AJIIPS_anticorr.pdf",
  volume =       "7",
  year =         "2001",
  keywords =     "genetic algorithms, genetic programming,
                 Anticorrelation, Artificial Neural Networks, committee
                 learning, Ensemble learning, fitness sharing,
                 diversity",
  abstract =     "Anticorrelation has been used in training neural
                 network ensembles. Negative correlation learning (NCL)
                 is the state of the art anticorrelation measure. We
                 present an alternative anticorrelation measure,
                 RTQRTNCL, which shows significant improvements on our
                 test examples for both artificial neural networks (ANN)
                 and genetic programming (GP) learning machines. We
                 analyse the behaviour of the negative correlation
                 measure and derive a theoretical explanation of the
                 improved performance of RTQRTNCL in larger ensembles.",
  notes =        "ANN UCI Australian credit card. GP 6-mux. Ensemble of
                 4 single hidden layer backprop perceptrons.

                 ",
}

Genetic Programming entries for R I (Bob) McKay Hussein A Abbass

Citations