Rajiv Senapati

Tri-level ensemble machine learning with bagging, boosting and stacking for medical data classification

This research proposes a tri-level ensemble approach that combines bagging, boosting, and stacking to classify various medical diseases and achieves an average accuracy of 97.00% on Pima, Yeast, Leukemia, Breast Cancer and Statlog datasets.