Advanced Ensemble Learning Meta-Framework

Design a comprehensive ensemble learning system that dynamically combines multiple machine learning models using advanced meta-learning techniques. Implement adaptive ensemble selection, weighted voting strategies, and performance-based model combination approaches. Develop a flexible architecture supporting heterogeneous model types, automated model selection, and uncertainty-aware ensemble generation. Include comprehensive performance tracking and interpretable ensemble composition reporting.