The purpose of this study is to introduce a gradient-boosting model that is robust to high-dimensional data and can produce a strong classifier by combining the predictors of many weak classifiers for ...

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 ...

Researchers developed a machine learning technique to predict obesity risk by analyzing sociodemographic, lifestyle, and health factors. The study, which achieved 79% accuracy, identified significant ...