Bootstrap Aggregating1

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  Bagging (Bootstrap Aggregating) Information Bagging (Bootstrap Aggregating) is a machine learning technique that combines multiple models trained on different subsets of the training data. Bagging is often used to reduce the variance and improve the stability of the predictions. Bagging samples the training data with replacement to create multiple bootstrap samples, each of which has the same size as the original dataset. Bagg.. Zettelkasten/Terminology Information 2023. 2. 23.