Bagging is the short-form for bootstrap aggregating. Bagging is actually a meta-algorithm that takes M subsamples from the initial dataset as inputs. Subsequently, the algorithm trains a predictive model on the subsamples. The final model is a product of averaging bootstrapped models and provides better results.
