Introduction: Ensemble methods represents a cornerstone in the realm of machine learning, embodying a powerful strategy that capitalizes on the collective intelligence of diverse learning algorithms to yield superior predictive performance. As the landscape of data-driven technologies evolves, the significance of ensemble methods continues to surge, reshaping the paradigms of model development and refining the art of predictive analytics. The genesis of ensemble methods traces back to seminal challenges such as the Netflix Prize in October 2006, a groundbreaking competition that captivated the data science community.
