Ensemble Methods

Ensemble methods are a type of machine learning technique that combines multiple models such as classifiers or experts to create an improved predictive performance. By combining these models, the system is able to address more complex problems and make better predictions than a single model alone. Ensemble methods have been widely used in many areas such as medical diagnostics, financial forecasting, and biomolecular analysis. They are useful in improving performance by reducing errors and increasing accuracy, allowing for more accurate predictions on data.