ensemble learner

An ensemble learner is a machine learning approach that combines multiple models to make better predictions than any individual model. Think of it like a panel of experts, each with their own opinion; by pooling their insights, the group can reach a more accurate decision. This method leverages the strengths and compensates for the weaknesses of different models, resulting in improved accuracy, robustness, and reliability in tasks such as classification or prediction. Ensemble methods are commonly used in areas like spam filtering, weather forecasting, and recommendation systems.