A genetic programming approach for bankruptcy prediction using a highly unbalanced database

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@InProceedings{alfaro-cid:evows07,

• author = "Eva Alfaro-Cid and Ken Sharman and Anna I. Esparcia-Alc\`azar",
• title = "A genetic programming approach for bankruptcy prediction using a highly unbalanced database",
• booktitle = "Applications of Evolutionary Computing, EvoWorkshops2007: {EvoCOMNET}, {EvoFIN}, {EvoIASP}, {EvoInteraction}, {EvoMUSART}, {EvoSTOC}, {EvoTransLog}",
• year = "2007",
• month = "11-13 " # apr,
• 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",
• series = "LNCS",
• volume = "4448",
• publisher = "Springer Verlag",
• address = "Valencia, Spain",
• pages = "169--178",
• keywords = "genetic algorithms, genetic programming, SVM",
• isbn13 = "978-3-540-71804-8",
• DOI = "doi:10.1007/978-3-540-71805-5_19",
• 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.",
• notes = "EvoWorkshops2007",

}

Genetic Programming entries for Eva Alfaro-Cid Kenneth C Sharman Anna Esparcia-Alcazar

Citations