GPF-CLASS: A Genetic Fuzzy Model for Classification
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Koshiyama:2013:CEC,
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article_id = "1709",
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author = "Adriano Koshiyama and Tatiana Escovedo and
Douglas Dias and Marley Vellasco and Ricardo Tanscheit",
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title = "GPF-CLASS: A Genetic Fuzzy Model for Classification",
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booktitle = "2013 IEEE Conference on Evolutionary Computation",
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volume = "1",
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year = "2013",
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month = jun # " 20-23",
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editor = "Luis Gerardo {de la Fraga}",
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pages = "3275--3282",
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address = "Cancun, Mexico",
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keywords = "genetic algorithms, genetic programming, multi-gene
genetic programming",
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isbn13 = "978-1-4799-0453-2",
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DOI = "doi:10.1109/CEC.2013.6557971",
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size = "8 pages",
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abstract = "This work presents a Genetic Fuzzy Classification
System (GFCS) called Genetic Programming Fuzzy
Classification System (GPF-CLASS). This model differs
from the traditional approach of GFCS, which uses the
metaheuristic as a way to learn if-then fuzzy rules.
This classical approach needs several changes and
constraints on the use of genetic operators, evaluation
and selection, which depends primarily on the
metaheuristic used. Genetic Programming makes this
implementation costly and explores few of its
characteristics and potentialities. The GPF-CLASS model
seeks for a greater integration with the metaheuristic:
Multi-Gene Genetic Programming (MGGP), exploring its
potential of terminals selection (input features) and
functional form and at the same time aims to provide
the user with a comprehension of the classification
solution. Tests with 22 benchmarks datasets for
classification have been performed and, as well as
statistical analysis and comparisons with others
Genetic Fuzzy Systems proposed in the literature.",
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notes = "CEC 2013 - A joint meeting of the IEEE, the EPS and
the IET.",
- }
Genetic Programming entries for
Adriano Soares Koshiyama
Tatiana Escovedo
Douglas Mota Dias
Marley Maria Bernardes Rebuzzi Vellasco
Ricardo Tanscheit
Citations