Ensemble Learning

Ensemble learning is a machine learning technique that combines multiple models to improve overall performance and accuracy. By aggregating the predictions of individual models, such as through voting or averaging, ensemble methods can reduce errors and enhance robustness compared to single-model approaches. This approach leverages the strengths of diverse models to achieve better generalization on unseen data.