Genetic Programming for Improved Receiver Operating Characteristics
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{langdon:2001:mcs,
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author = "W. B. Langdon and B. F. Buxton",
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title = "Genetic Programming for Improved Receiver Operating
Characteristics",
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booktitle = "Second International Conference on Multiple Classifier
System",
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year = "2001",
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editor = "Josef Kittler and Fabio Roli",
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volume = "2096",
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series = "LNCS",
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pages = "68--77",
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address = "Cambridge",
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month = "2-4 " # jul,
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publisher = "Springer Verlag",
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keywords = "genetic algorithms, genetic programming, data fusion,
data mining, knowledge discovery, Receiver Operating
Characteristics, ensemble of classifiers, size fair
crossover, cost-sensitive, cost trade off, non-uniform
penalty",
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ISBN = "3-540-42284-6",
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URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/wbl_mcs2001.pdf",
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URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/wbl_mcs2001.ps.gz",
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DOI = "doi:10.1007/3-540-48219-9_7",
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size = "10 pages",
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abstract = "Genetic programming (GP) can automatically fuse given
classifiers to produce a combined classifier whose
Receiver Operating Characteristics (ROC) are better
than [Scott et al. 1998]'s \cite{scott:1998:BMVC}
``Maximum Realisable Receiver Operating
Characteristics'' (MRROC). I.e. better than their
convex hull. This is demonstrated on artificial,
medical and satellite image processing bench marks.",
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notes = "http://www.diee.unica.it/mcs/ Technique in
\cite{langdon:2001:gROC} used to combine different
classifiers on trained on different data.",
- }
Genetic Programming entries for
William B Langdon
Bernard Buxton
Citations