Gradient boosting decision tree (GBDT) for firm failure prediction is proposed. Sensitivity analysis and model interpretability of GBDT are analyzed and validated. GDBT, bagging, Adaboost, Random ...

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 ...