Strong Typing, Variable Reduction and Bloat Control for Solving the Bankruptcy Prediction Problem Using Genetic Programming
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- @InCollection{series/sci/Alfaro-CidCSE08,
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title = "Strong Typing, Variable Reduction and Bloat Control
for Solving the Bankruptcy Prediction Problem Using
Genetic Programming",
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author = "Eva Alfaro-Cid and Alberto Cuesta-Canada and
Ken Sharman and Anna Esparcia-Alcazar",
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bibdate = "2008-08-26",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/series/sci/sci100.html#Alfaro-CidCSE08",
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booktitle = "Natural Computing in Computational Finance",
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publisher = "Springer",
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year = "2008",
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volume = "100",
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editor = "Anthony Brabazon and Michael O'Neill",
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isbn13 = "978-3-540-77476-1",
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pages = "161--185",
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series = "Studies in Computational Intelligence",
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DOI = "doi:10.1007/978-3-540-77477-8_9",
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chapter = "9",
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keywords = "genetic algorithms, genetic programming, STGP, SVM",
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size = "29 pages",
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abstract = "In this chapter we present the application of a
genetic programming (GP) algorithm to the problem of
bankruptcy prediction. To carry out the research we
have used a database that includes extensive
information (not only economic) from the companies. In
order to handle the different data types we have used
Strongly Typed GP and variable reduction. Also, bloat
control has been implemented to obtain comprehensible
classification models. For comparison purposes we have
solved the same problem using a support vector machine
(SVM). GP has achieved very satisfactory results,
improving those obtained with the SVM.",
- }
Genetic Programming entries for
Eva Alfaro-Cid
Alberto Cuesta Canada
Kenneth C Sharman
Anna Esparcia-Alcazar
Citations