Genetic Network Programming for Fuzzy Association Rule-Based Classification
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Taboada:2009:cec,
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author = "Karla Taboada and Shingo Mabu and Eloy Gonzales and
Kaoru Shimada and Kotaro Hirasawa",
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title = "Genetic Network Programming for Fuzzy Association
Rule-Based Classification",
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booktitle = "2009 IEEE Congress on Evolutionary Computation",
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year = "2009",
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editor = "Andy Tyrrell",
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pages = "2387--2394",
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address = "Trondheim, Norway",
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month = "18-21 " # may,
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organization = "IEEE Computational Intelligence Society",
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publisher = "IEEE Press",
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isbn13 = "978-1-4244-2959-2",
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file = "P662.pdf",
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DOI = "doi:10.1109/CEC.2009.4983239",
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abstract = "This paper presents a novel classification approach
that integrates fuzzy classification rules and Genetic
Network Programming (GNP). A fuzzy discretization
technique is applied to transform the dataset,
particularly for dealing with quantitative attributes.
GNP is an evolutionary optimization technique that uses
directed graph structures as genes instead of strings
and trees of Genetic Algorithms (GA) and Genetic
Programming (GP), respectively. This feature
contributes to creating quite compact programs and
implicitly memorizing past action sequences. Therefore,
in the proposed method, taking the GNP's structure into
account 1) extraction of fuzzy classification rules is
done without identifying frequent itemsets used in most
Apriori-based data mining algorithms, 2) calculation of
the support, confidence and Χ2 value is
made in order to quantify the significance of the rules
to be integrated into the classifier, 3) fuzzy
membership values are used for fuzzy classification
rules extraction, 4) fuzzy rules are mined through
generations and stored in a general pool. On the other
hand, parameters of the membership functions are
evolved by non-uniform mutation in order to perform a
more global search in the space of candidate membership
functions. The performance of our algorithm has been
compared with other relevant algorithms and the
experimental results have shown the advantages and
effectiveness of the proposed model.",
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keywords = "genetic algorithms, genetic programming, genetic
network programming",
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notes = "CEC 2009 - A joint meeting of the IEEE, the EPS and
the IET. IEEE Catalog Number: CFP09ICE-CDR",
- }
Genetic Programming entries for
Karla Taboada
Shingo Mabu
Eloy Gonzales
Kaoru Shimada
Kotaro Hirasawa
Citations