GAP: Constructing and Selecting Features with Evolutionary Computation
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InCollection{smith:2004:ECDM,
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author = "Matthew G. Smith and Larry Bull",
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title = "GAP: Constructing and Selecting Features with
Evolutionary Computation",
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booktitle = "Evolutionary Computing in Data Mining",
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publisher = "Springer",
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year = "2004",
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editor = "Ashish Ghosh and Lakhmi C. Jain",
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volume = "163",
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series = "Studies in Fuzziness and Soft Computing",
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chapter = "3",
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pages = "41--56",
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keywords = "genetic algorithms, genetic programming, ADFs",
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ISBN = "3-540-22370-3",
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URL = "http://www.springeronline.com/sgw/cda/frontpage/0,11855,5-175-22-33980376-0,00.html",
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DOI = "doi:10.1007/3-540-32358-9_3",
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abstract = "The use of machine learning techniques to
automatically analyze data for information is becoming
increasingly widespread. In this chapter we examine the
use of Genetic Programming and a Genetic Algorithm to
pre-process data before it is classified using the C4.5
decision tree learning algorithm. Genetic Programming
is used to construct new features from those available
in the data, a potentially significant process for data
mining since it gives consideration to hidden
relationships between features. A Genetic Algorithm is
used to determine which set of features is the most
predictive. Using ten well-known data sets we show that
our approach, in comparison to C4.5 alone, provides
marked improvement in a number of cases.",
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notes = "GA+GP system used to preprocess ten UCI datasets
constructing and selecting new features before using
C4.5",
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size = "16 pages",
- }
Genetic Programming entries for
Matthew G Smith
Larry Bull
Citations