A Boosted Ensemble Framework with Bio-Inspired Optimization for Multivariate Classification of Structured Data
Anber Abraheem Shlash Mohammad·Prakhar Tomar·Khaleel Ibrahim Al-Daoud·Asokan Vasudevan·Roopa Traisa·Arshdeep Singh Dhaliwal·Rajashree Panigrahi·Jitendra Singh Chauhan·Suleiman Ibrahim Mohammad
This study presents a comprehensive machine learning framework that integrates advanced ensemble classifiers with bio-inspired optimization to perform high-accuracy classification of multivariate structured data. The proposed approach is applied to classify countries based on health, demographic, and economic indicators. Specifically, three state-of-the-art boosting models, Extreme Gradient Boosting (XGBoost), LightGBM, and Histogram-Based Gradient Boosting, are evaluated for their predictive pe