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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Alfaro-Cid, E., Sharman, K., Esparcia-Alcázar, A.I. (2007). A Genetic Programming Approach for Bankruptcy Prediction Using a Highly Unbalanced Database. In: Giacobini, M. (eds) Applications of Evolutionary Computing. EvoWorkshops 2007. Lecture Notes in Computer Science, vol 4448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71805-5_19
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DOI: https://doi.org/10.1007/978-3-540-71805-5_19
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