Anti-correlation: A Diversity Promoting Mechanisms in Ensemble Learning
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @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