Application of Genetic Programming to Induction of Linear Classification Trees
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{bot:2000:GPilct,
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author = "Martijn C. J. Bot and William B. Langdon",
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title = "Application of Genetic Programming to Induction of
Linear Classification Trees",
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booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
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year = "2000",
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editor = "Riccardo Poli and Wolfgang Banzhaf and
William B. Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
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volume = "1802",
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series = "LNCS",
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pages = "247--258",
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address = "Edinburgh",
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publisher_address = "Berlin",
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month = "15-16 " # apr,
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organisation = "EvoNet",
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publisher = "Springer-Verlag",
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keywords = "genetic algorithms, genetic programming: Poster",
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ISBN = "3-540-67339-3",
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URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/martijn/bot.eurogp2000.19jan.ps.gz",
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URL = "http://citeseer.ist.psu.edu/318695.html",
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DOI = "doi:10.1007/978-3-540-46239-2_18",
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abstract = "A common problem in datamining is to find accurate
classifiers for a dataset. For this purpose, genetic
programming (GP) is applied to a set of benchmark
classification problems. Using GP we are able to induce
decision trees with a linear combination of variables
in each function node. A new representation of decision
trees using strong typing in GP is introduced. With
this representation it is possible to let the GP
classify into any number o f classes. Results indicate
that GP can be applied successfully to classification
problems. Comparisons with current state-of-the-art
algorithms in machine learning are presented and areas
of future research are identified.",
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notes = "See also \cite{bot:1999:GPilct} EuroGP'2000, part of
\cite{poli:2000:GP}",
- }
Genetic Programming entries for
Martijn C J Bot
William B Langdon
Citations