Training Binary GP Classifiers Efficiently: a Pareto-coevolutionary Approach
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{eurogp07:lemczyk,
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author = "Michal Lemczyk and Malcolm I. Heywood",
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title = "Training Binary GP Classifiers Efficiently: a
Pareto-coevolutionary Approach",
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editor = "Marc Ebner and Michael O'Neill and Anik\'o Ek\'art and
Leonardo Vanneschi and Anna Isabel Esparcia-Alc\'azar",
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booktitle = "Proceedings of the 10th European Conference on Genetic
Programming",
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publisher = "Springer",
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series = "Lecture Notes in Computer Science",
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volume = "4445",
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year = "2007",
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address = "Valencia, Spain",
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month = "11-13 " # apr,
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pages = "229--240",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "3-540-71602-5",
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isbn13 = "978-3-540-71602-0",
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DOI = "doi:10.1007/978-3-540-71605-1_21",
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abstract = "The conversion and extension of the Incremental
Pareto-Coevolution Archive algorithm (IPCA) into the
domain of Genetic Programming classification is
presented. In particular, the coevolutionary aspect of
the IPCA algorithm is used to simultaneously evolve a
subset of the training data that provides distinctions
between candidate classifiers. Empirical results
indicate that such a scheme significantly reduces the
computational overhead of fitness evaluation on large
binary classification data sets. Moreover, unlike the
performance of GP classifiers trained using alternative
subset selection algorithms, the proposed
Pareto-coevolutionary approach is able to match or
better the classification performance of GP trained
over all training exemplars. Finally, problem
decomposition appears as a natural consequence of
assuming a Pareto model for coevolution. In order to
make use of this property a voting scheme is used to
integrate the results of all classifiers from the
Pareto front, post training.",
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notes = "Part of \cite{ebner:2007:GP} EuroGP'2007 held in
conjunction with EvoCOP2007, EvoBIO2007 and
EvoWorkshops2007",
- }
Genetic Programming entries for
Michal Lemczyk
Malcolm Heywood
Citations