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 ...

A gradient boosting machine model performed best among five machine learning models tested for predicting delirium, according to findings recently published in JAMA Network Open. “Existing ...

A prediction model that would facilitate early recognition of patients at risk for SAP is crucial for improvement of patient prognosis. Objectives: The aim of this study was to evaluate the accuracy ...

This article investigates a computationally simple variant of boosting, L₂Boost, which is constructed from a functional gradient descent algorithm with the L₂-loss function. Like other boosting ...