Most studies in credit scoring use balanced samples which contain the same proportion of credible and non credible applicants. However, this is not a true distribution in the population, because the proportion of credible clients is quite higher than the proportion of non credible ones.

        The aim of the paper is to study the effect of the sample structure on the performance of ensemble classification trees in discriminating of the individual borrowers into the groups of creditworthy or non-creditworthy clients.

       Aggregated classification trees are constructed employing two ensemble methods: Adaboost and Bagging. The research is conducted employing actual data regarding the individual borrowers that got a mortgage credit in one of the commercial banks that operate in Poland.

1. FULLTEXT: A Study on the Stability of Ensemble Trees: Example of the Polish Credit Scoring Application, Microsoft Office Document, 0.1MB

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