Genetic programming for feature selection in business failure prediction. Comparison of the use of financial variables and economic environment variables

Bibliographic citation

Beade, A. Rodríguez López, M. & Santos, J. (2024). Genetic programming for feature selection in business failure prediction. Comparison of the use of financial variables and economic environment variables. International Conference on INnovations in Intelligent SysTems and Applications (INISTA), Craiova, Romania, 2024, pp. 1-6. DOI:0.1109/INISTA62901.2024.10683824.

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Abstract

[Abstract]: In this work we have experimented with the use of genetic programming as a feature selection method as well as a classifier to obtain business failure prediction models with different prediction temporal horizons. In the prediction models, a wide set of explanatory variables has been used, all of them based on the annual accounts of the company. In addition, an extended set of explanatory variables incorporating variables from the economic environment has been considered. Comparison of the prediction results between these alternatives shows a trend towards better results using the feature selection process, while there is no trend towards better results using economic environment variables.

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