Evolutionary Constructive Induction
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @Article{10.1109/TKDE.2005.182,
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author = "Mohammed Muharram and George D. Smith",
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title = "Evolutionary Constructive Induction",
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journal = "IEEE Transactions on Knowledge and Data Engineering",
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volume = "17",
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number = "11",
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year = "2005",
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pages = "1518--1528",
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publisher = "IEEE Computer Society",
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address = "Los Alamitos, CA, USA",
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month = nov,
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keywords = "genetic algorithms, genetic programming, Feature
construction, classification",
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ISSN = "1041-4347",
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DOI = "doi:10.1109/TKDE.2005.182",
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abstract = "Feature construction in classification is a
preprocessing step in which one or more new attributes
are constructed from the original attribute set, the
object being to construct features that are more
predictive than the original feature set. Genetic
programming allows the construction of nonlinear
combinations of the original features. We present a
comprehensive analysis of genetic programming (GP) used
for feature construction, in which four different
fitness functions are used by the GP and four different
classification techniques are subsequently used to
build the classifier. Comparisons are made of the error
rates and the size and complexity of the resulting
trees. We also compare the overall performance of GP in
feature construction with that of GP used directly to
evolve a decision tree classifier, with the former
proving to be a more effective use of the evolutionary
paradigm.",
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notes = "
",
- }
Genetic Programming entries for
Mohammed A Muharram
George D Smith
Citations