Using boosting to prune bagging ensembles

Boosting is used to determine the order in which classifiers are aggregated in a bagging ensemble. Early stopping in the aggregation of the classifiers in the ordered bagging ensemble allows the identification of subensembles that require less memory for storage, have a faster classification speed and can perform better than the original bagging ensemble. Furthermore, ensemble pruning does not seem to deteriorate the robust performance of bagging in noisy classification tasks.