A Genetic Programming Approach for Bankruptcy Prediction Using a Highly Unbalanced Database

Authors:
Eva Alfaro-Cid;Ken Sharman;Anna I. Esparcia-Alcázar
Affiliations:
Instituto Tecnológico de Informática, Universidad Politécnica de Valencia,Camino de Vera s/n, 46022 Valencia, Spain;Instituto Tecnológico de Informática, Universidad Politécnica de Valencia,Camino de Vera s/n, 46022 Valencia, Spain;Instituto Tecnológico de Informática, Universidad Politécnica de Valencia,Camino de Vera s/n, 46022 Valencia, Spain
Venue:
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Year:
2009

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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.