Answer / Saurabh Gaur

Bagging (Bootstrap Aggregating) is an ensemble learning technique that combines multiple models to improve the predictive performance and reduce overfitting. Bagging trains multiple models on different subsets of the training data created by random sampling with replacement, reducing correlation among the individual models.

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