Ensemble Classifiers: AdaBoost and Orthogonal Evolution of Teams
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InCollection{Soule:2010:GPTP,
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author = "Terence Soule and Robert B. Heckendorn and
Brian Dyre and Roger Lew",
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title = "Ensemble Classifiers: {AdaBoost} and Orthogonal
Evolution of Teams",
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booktitle = "Genetic Programming Theory and Practice VIII",
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year = "2010",
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editor = "Rick Riolo and Trent McConaghy and
Ekaterina Vladislavleva",
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series = "Genetic and Evolutionary Computation",
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volume = "8",
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address = "Ann Arbor, USA",
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month = "20-22 " # may,
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publisher = "Springer",
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chapter = "4",
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pages = "55--69",
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keywords = "genetic algorithms, genetic programming, ensembles,
teams, classifiers, OET, AdaBoost",
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isbn13 = "978-1-4419-7746-5",
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URL = "http://www.springer.com/computer/ai/book/978-1-4419-7746-5",
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DOI = "doi:10.1007/978-1-4419-7747-2_4",
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abstract = "AdaBoost is one of the most commonly used and most
successful approaches for generating ensemble
classifiers. However, AdaBoost is limited in that it
requires independent training cases and can only use
voting as a cooperation mechanism. This paper compares
AdaBoost to Orthogonal Evolution of Teams (OET), an
approach for generating ensembles that allows for a
much wider range of problems and cooperation
mechanisms. The set of test problems includes problems
with significant amounts of noise in the form of
erroneous training cases and problems with adjustable
levels of epistasis. The results demonstrate that OET
is a suitable alternative to AdaBoost for generating
ensembles. Over the set of all tested problems OET with
a hierarchical cooperation mechanism, rather than
voting, is slightly more likely to produce better
results. This is most apparent on the problems with
very high levels of noise - suggesting that the
hierarchical approach is less subject to over-fitting
than voting techniques. The results also suggest that
there are specific problems and features of problems
that make thembetter suited for different training
algorithms and different cooperation mechanisms.",
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notes = "part of \cite{Riolo:2010:GPTP}",
- }
Genetic Programming entries for
Terence Soule
Robert B Heckendorn
Brian P Dyre
Roger Lew
Citations