A genetic programming approach for bankruptcy prediction using a highly unbalanced database
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- @InProceedings{alfaro-cid:evows07,
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author = "Eva Alfaro-Cid and Ken Sharman and
Anna I. Esparcia-Alc\`azar",
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title = "A genetic programming approach for bankruptcy
prediction using a highly unbalanced database",
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booktitle = "Applications of Evolutionary Computing,
EvoWorkshops2007: {EvoCOMNET}, {EvoFIN}, {EvoIASP},
{EvoInteraction}, {EvoMUSART}, {EvoSTOC},
{EvoTransLog}",
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year = "2007",
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month = "11-13 " # apr,
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editor = "Mario Giacobini and Anthony Brabazon and
Stefano Cagnoni and Gianni A. {Di Caro} and Rolf Drechsler and
Muddassar Farooq and Andreas Fink and
Evelyne Lutton and Penousal Machado and Stefan Minner and
Michael O'Neill and Juan Romero and Franz Rothlauf and
Giovanni Squillero and Hideyuki Takagi and A. Sima Uyar and
Shengxiang Yang",
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series = "LNCS",
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volume = "4448",
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publisher = "Springer Verlag",
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address = "Valencia, Spain",
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pages = "169--178",
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keywords = "genetic algorithms, genetic programming, SVM",
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isbn13 = "978-3-540-71804-8",
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DOI = "doi:10.1007/978-3-540-71805-5_19",
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abstract = "in this paper we present the application of a genetic
programming algorithm to the problem of bankruptcy
prediction. To carry out the research we have used a
database of Spanish companies. The database has two
important drawbacks: the number of bankrupt companies
is very small when compared with the number of healthy
ones (unbalanced data) and a considerable number of
companies have missing data. For comparison purposes we
have solved the same problem using a support vector
machine. Genetic programming has achieved very
satisfactory results, improving those obtained with the
support vector machine.",
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notes = "EvoWorkshops2007",
- }
Genetic Programming entries for
Eva Alfaro-Cid
Kenneth C Sharman
Anna Esparcia-Alcazar
Citations