Design of Decision Trees through Integration of C4.5 and GP
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Oka:2000:DDTICGP,
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author = "Shin'ichi Oka and Qiangfu Zhao",
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title = "Design of Decision Trees through Integration of {C4.5}
and GP",
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booktitle = "Proceedings of the fourth Japan-Australia Joint
Workshop on Intelligent and Evolutionary Systems",
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year = "2000",
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editor = "Akira Namatame {et al.}",
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pages = "128--135",
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address = "Shonan Village Center, Hayama, Japan",
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month = "31 " # oct # " - 2 " # nov,
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publisher = "Japan. National Defence Academy ; Australia.
Australian Defence Force Academy",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "0-7317-0504-1",
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URL = "http://www.u-aizu.ac.jp/~qf-zhao/CONTRIBUTION/oka-zhao.ps.Z",
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URL = "http://130.203.133.150/viewdoc/summary?doi=10.1.1.23.3179",
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catalogue-url = "http://nla.gov.au/nla.cat-vn1175103",
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size = "6 pages",
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abstract = "C4.5 is one of the tools for designing decision trees
(DTs) from training examples. In most cases, C4.5 can
generate near optimal DTs when the training data are
given all together. However, if the training data are
given incrementally, C4.5 cannot be used. In this case,
genetic programming (GP) might be a better choice.
Actually, GP can be considered as a DT-breeder in which
good DTs can be generated automatically through
evolution. In GP based DT design, the training examples
can be given all together or incrementally, provided
that the fitness of the tree is properly defined. This
of course does NOT mean that the GP based approach is
BETTER than C4.5 because DTs obtained by GP are usually
very large and complex. In this paper, we try to
integrate C4.5 and GP in such a way that each
individual is initialised by C4.5 using part of the
training examples. By so doing, we can have relatively
good DTs from the very beginning, and use them while
waiting for better DTs to emerge. To show the
effectiveness of this kind of integration, we conducted
some experiments with a digit recognition problem.
Experimental results show that smaller DTs with higher
recognition rates can always be obtained through
integration of C4.5 and GP. However, as the evolution
continues, DTs obtained by GP (with random
initialisation) tend to have almost the same
recognition ability as those obtained by C4.5+GP.",
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notes = "Selected Refereed Publications of Qiangfu Zhao and His
Students
National library of Australia
http://catalogue.nla.gov.au/Record/1175103
http://www.uco.es/grupos/kdis/kdiswiki/gp/GP_bibliography_bib.html#Oka:2000:DDTICGP",
- }
Genetic Programming entries for
Shin'ichi Oka
Qiangfu Zhao
Citations