Bankruptcy prediction has been a subject of interests for almost a century
and it still ranks high among hottest topics in economics. The aim of predicting
financial distress is to develop a predictive model that combines various
econometric measures and allows to foresee a financial condition of a firm.
The purpose of the bankruptcy prediction is to assess the financial condition
of a company and its future perspectives within the context of longterm
operation on the market (Zieba, et al., 2016).
Acknowledgements
We thank Sebastian Tomczak for providing this dataset. The training and testing data are processed based on the Polish companies bankruptcy data Data Set available at UCI Machine Learning Repository. Data has been preprocessed by removing missing values and standardizing columns. The training and testing data are randomly selected from the whole data sets. Reference: Zieba, Maciej and Tomczak, Sebastian K and Tomczak, Jakub M (2016), Ensemble Boosted Trees with Synthetic Features Generation in Application to Bankruptcy Prediction, Expert Systems with Applications.