The study tested four machine learning algorithms to analyze the data: Gradient tree boosting, random forest, classification and regression trees, or CART, and support vector machine.

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 ...

Gradient-boosting trees. Gradient boosting is an ensemble machine learning model to form robust predictions on the basis of the integrated predictions of multiple simpler trees. 22 Although each tree ...