Soil Classification Using GATREE
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gp-bibliography.bib Revision:1.8081
- @Article{Bhargavi:2010:IJCSIT,
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title = "Soil Classification Using {GATREE}",
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author = "P. Bhargavi and S. Jyothi",
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journal = "International Journal of Computer Science \&
Information Technology",
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year = "2010",
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volume = "2",
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number = "5",
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pages = "184--191",
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keywords = "genetic algorithms, genetic programming, data mining,
soil profile, soil database, classification",
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ISSN = "09754660",
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URL = "http://airccse.org/journal/jcsit/1010ijcsit14.pdf",
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DOI = "doi:10.5121/ijcsit.2010.2514",
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publisher = "Academy \& Industry Research Collaboration Centre
(AIRCC)",
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bibsource = "OAI-PMH server at www.doaj.org",
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oai = "oai:doaj-articles:62c4c972981e7958ba9ff79981358355",
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size = "8 pages",
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abstract = "This paper details the application of a genetic
programming framework for classification of decision
tree of Soil data to classify soil texture. The
database contains measurements of soil profile data. We
have applied GATree for generating classification
decision tree. GATree is a decision tree builder that
is based on Genetic Algorithms(GAs). The idea behind it
is rather simple but powerful. Instead of using
statistic metrics that are biased towards specific
trees we use a more flexible, global metric of tree
quality that try to optimise accuracy and size. GATree
offers some unique features not to be found in any
other tree inducers while at the same time it can
produce better results for many difficult problems.
Experimental results are presented which illustrate the
performance of generating best decision tree for
classifying soil texture for soil data set.",
- }
Genetic Programming entries for
P Bhargavi
S Jyothi
Citations