Ensemble Learning1

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  Ensemble learning Information Ensemble learning combines the predictions of multiple models to achieve better accuracy than a single model. There are three types of ensemble learning: bagging, boosting, and stacking. Bagging (bootstrap aggregating) involves training multiple models on different subsets of the training data and then averaging their predictions. Boosting involves training multiple models in sequenc.. Zettelkasten/Terminology Information 2023. 3. 15.