Explainable diabetes prediction using a stacked ensemble framework
A robust and explainable machine learning framework based on a stacked ensemble model that uses Random Forest, Support Vector Machine, and Gradient Boosting as base learners and Catboost as the meta-learner to support more informed and trustworthy decision-making in healthcare applications is presented.