A Parallel Genetic Programming Algorithm for Classification
Created by W.Langdon from
gp-bibliography.bib Revision:1.7989
- @InProceedings{conf/hais/CanoZV11,
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author = "Alberto Cano and Amelia Zafra and Sebastian Ventura",
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title = "A Parallel Genetic Programming Algorithm for
Classification",
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booktitle = "Proceedings of the 6th International Conference on
Hybrid Artificial Intelligent Systems (HAIS 2011) Part
{I}",
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year = "2011",
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editor = "Emilio Corchado and Marek Kurzynski and
Michal Wozniak",
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volume = "6678",
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series = "Lecture Notes in Computer Science",
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pages = "172--181",
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address = "Wroclaw, Poland",
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month = may # " 23-25",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, KEEL, JCLEC",
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isbn13 = "978-3-642-21218-5",
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DOI = "doi:10.1007/978-3-642-21219-2_23",
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size = "10 pages",
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abstract = "In this paper a Grammar Guided Genetic
Programming-based method for the learning of rule-based
classification systems is proposed. The method learns
disjunctive normal form rules generated by means of a
context-free grammar. The individual constitutes a rule
based decision list that represents the full
classifier. To overcome the problem of computational
time of this system, it parallelises the evaluation
phase reducing significantly the computation time.
Moreover, different operator genetics are designed to
maintain the diversity of the population and get a
compact set of rules. The results obtained have been
validated by the use of non-parametric statistical
tests, showing a good performance in terms of accuracy
and interpretability.",
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notes = "UCI",
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affiliation = "Department of Computing and Numerical Analysis,
University of Cordoba, 14071 Cordoba, Spain",
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bibdate = "2011-06-06",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/hais/hais2011-1.html#CanoZV11",
- }
Genetic Programming entries for
Alberto Cano Rojas
Amelia Zafra Gomez
Sebastian Ventura
Citations