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I am very new to Machine Learning I know i should use Decision Tree for bagging model because of its high variance. why cant we use any other algorithms for bagging ? if we can use any other algorithms for bagging which are those? and how can we use it ?

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You can use any base algorithm for bagging, there are no restrictions.

Since the bagging strategy is to reduce the variance of the learning algorithm through averaging, it tends to have the largest impact on models that are prone to high variance. So you'll see deep decision trees bagged quite often, but linear regression only rarely.

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