Evolving ensembles in multi-objective genetic programming for classification with unbalanced data
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gp-bibliography.bib Revision:1.7954
- @InProceedings{Bhowan:2011:GECCO,
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author = "Urvesh Bhowan and Mark Johnston and Mengjie Zhang",
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title = "Evolving ensembles in multi-objective genetic
programming for classification with unbalanced data",
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booktitle = "GECCO '11: Proceedings of the 13th annual conference
on Genetic and evolutionary computation",
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year = "2011",
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editor = "Natalio Krasnogor and Pier Luca Lanzi and
Andries Engelbrecht and David Pelta and Carlos Gershenson and
Giovanni Squillero and Alex Freitas and
Marylyn Ritchie and Mike Preuss and Christian Gagne and
Yew Soon Ong and Guenther Raidl and Marcus Gallager and
Jose Lozano and Carlos Coello-Coello and Dario Landa Silva and
Nikolaus Hansen and Silja Meyer-Nieberg and
Jim Smith and Gus Eiben and Ester Bernado-Mansilla and
Will Browne and Lee Spector and Tina Yu and Jeff Clune and
Greg Hornby and Man-Leung Wong and Pierre Collet and
Steve Gustafson and Jean-Paul Watson and
Moshe Sipper and Simon Poulding and Gabriela Ochoa and
Marc Schoenauer and Carsten Witt and Anne Auger",
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isbn13 = "978-1-4503-0557-0",
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pages = "1331--1338",
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keywords = "genetic algorithms, genetic programming",
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month = "12-16 " # jul,
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organisation = "SIGEVO",
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address = "Dublin, Ireland",
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DOI = "doi:10.1145/2001576.2001756",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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abstract = "Machine learning algorithms can suffer a performance
bias when data sets are unbalanced. This paper proposes
a Multi-objective Genetic Programming approach using
negative correlation learning to evolve accurate and
diverse ensembles of non-dominated solutions where
members vote on class membership. We also compare two
popular Pareto-based fitness schemes on the
classification tasks. We show that the evolved
ensembles achieve high accuracy on both classes using
six unbalanced binary data sets, and that this
performance is usually better than many of its
individual members.",
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notes = "Also known as \cite{2001756} GECCO-2011 A joint
meeting of the twentieth international conference on
genetic algorithms (ICGA-2011) and the sixteenth annual
genetic programming conference (GP-2011)",
- }
Genetic Programming entries for
Urvesh Bhowan
Mark Johnston
Mengjie Zhang
Citations