Ensemble methods are machine-learning techniques that combine the predictions of multiple models to produce a single result. Instead of relying on one model, an ensemble uses several models and combines their outputs through voting, averaging, or another learned rule. This can make predictions more stable and, when the models contribute useful and varied information, more […]