The use of Bayesian Networks in the prediction of bankruptcy
The purpose of this paper is to compare the development of Bayesian Network models: naïveBayesian network (NBN) and a maximum weight spanning tree (MWST) in forecasting thefailure of the Tunisian companies. Using a sample of 130 small and medium Tunisiancompanies and a battery of 9 financial ratios calculated for the 2005-2012 period, it can beconcluded that, for a classification problem, supervised learning with naïve architecture ismore appropriate and gives more relevant results than an unsupervised learning model with amaximum weight spanning tree.
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ZAMMEL, Madiha; KHOUFI, Walid. 2020. The use of Bayesian Networks in the prediction of bankruptcy. Revue Française d'Economie et de Gestion. https://africanscientificindex.com/articles/revue-francaise-d-economie-et-de-gestion-the-use-of-bayesian-networks-in-the-prediction-of-bankruptcy
Revue Française d'Economie et de Gestion (2020)
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