I am learning about bagging ensemble techniques like Random Forests and the concepts of Row Sampling, Pasting, Random Subspace, and Random Patches Methods. What I understood is that bagging involves the creation of a bootstrap dataset from the original dataset. As per wikipedia the size of the bootstrap dataset should be equal to the original dataset. Compared with the definition of bootstrapping in statistics, a bootstrap dataset is a smaller sample of the original population.
I want to confirm if this concept of bootstrapping is different when we talk about Bagging versus statistics, as I have explained above?