Genetic Programming for Data Classification: Partitioning the Search Space
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @InProceedings{eggermont:2004:sac,
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author = "Jeroen Eggermont and Joost N. Kok and
Walter A. Kosters",
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title = "Genetic Programming for Data Classification:
Partitioning the Search Space",
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booktitle = "Proceedings of the 2004 Symposium on applied computing
(ACM SAC'04)",
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year = "2004",
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pages = "1001--1005",
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address = "Nicosia, Cyprus",
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month = "14-17 " # mar,
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keywords = "genetic algorithms, genetic programming, data
classification",
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URL = "http://www.liacs.nl/~kosters/SAC2003final.pdf",
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DOI = "doi:10.1145/967900.968104",
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size = "5 pages",
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abstract = "When Genetic Programming is used to evolve decision
trees for data classification, search spaces tend to
become extremely large. We present several methods
using techniques from the field of machine learning to
refine and thereby reduce the search space sizes for
decision tree evolvers. We will show that these
refinement methods improve the classification
performance of our algorithms.",
- }
Genetic Programming entries for
Jeroen Eggermont
Joost Kok
Walter A Kosters
Citations