In this paper, we employ a gradient-boosting decision-tree (GBDT) method to improve firm failure prediction and explain how to better analyze the relative importance of each financial variable.

We then compare the performances of seven supervised models, i.e., naive Bayes, logistic, linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA), as well as tree-based methods ...