An ensemble model is a machine learning technique that combines the predictions of multiple individual models to improve overall performance by leveraging diversity among the base models.
Ensemble methods combine results from multiple ML models instead of relying on a single model. The idea is that this combination provides more accuracy. An analogy is consulting multiple doctors for a diagnosis, enhancing accuracy compared to a single doctor’s opinion.
What are the main techniques used to combine decision trees for a more accurate model (ensemble techniques)?;; The main ensemble techniques for combining decision trees are Boosting algorithms Bagging techniques.