Learning acyclic rules based on Chaining Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{conf/aiccsa/ShumLW06,
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author = "Wing-Ho Shum and Kwong-Sak Leung and Man Leung Wong",
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title = "Learning acyclic rules based on Chaining Genetic
Programming",
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booktitle = "The 4th ACS/IEEE International Conference on Computer
Systems and Applications (AICCSA-06)",
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year = "2006",
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editor = "Michael A. Langston and Mohsen Guizani",
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pages = "960--967",
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address = "Dubai",
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month = mar # " 8-11",
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publisher = "IEEE",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "1-4244-0211-5",
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URL = "http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=33913&arnumber=1618469&count=182&index=144",
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DOI = "doi:10.1109/AICCSA.2006.205204",
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size = "8 pages",
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abstract = "Multi-class problem is the class of problems having
more than one classes in the data set. Bayesian Network
(BN) is a well-known algorithm handling the multi-class
problem and is applied to different areas. But BN
cannot handle continuous values. In contrast, Genetic
Programming (GP) can handle continuous values and
produces classification rules. However, GP is possible
to produce cyclic rules representing tautologic, in
which are useless for inference and expert systems.
Co-evolutionary Rule-chaining Genetic Programming
(CRGP) is the first variant of GP handling the
multi-class problem and produces acyclic classification
rules [16]. It employs backward chaining inference to
carry out classification based on the acquired acyclic
rule set. It can handle multi-classes; it can avoid
cyclic rules; it can handle input attributes with
continuous values; and it can learn complex
relationships among the attributes. In this paper, we
propose a novel algorithm, the Chaining Genetic
Programming (CGP) learning a set of acyclic rules and
to produce better results than the CRGP's. The
experimental results demonstrate that the proposed
algorithm has the shorter learning process and can
produce more accurate acyclic classification rules.",
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notes = "http://www.cs.utk.edu/aiccsa06/",
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bibdate = "2009-06-09",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/aiccsa/aiccsa2006.html#ShumLW06",
- }
Genetic Programming entries for
Wing-Ho Shum
Kwong-Sak Leung
Man Leung Wong
Citations