What is Ensemble?

Ensemble methods are machine learning techniques that combine several base models to produce one optimal predictive model. Ensemble methods are used to improve the stability and accuracy of machine learning algorithms. Common ensemble methods include Bagging, Boosting, and Stacking. They are widely used in various applications like fraud detection, medical diagnosis, and financial forecasting due to their ability to reduce overfitting and improve generalization.