Two ensemble methods, bagging and boosting, were investigated for improving algorithm performance. Our results confirmed the theoretical explanation  that bagging improves unstable, but not stable, learning algorithms. While boosting enhanced accuracy of a weak learner, its behavior is subject to the characteristics of each learning algorithm.
Additional Publication Details
Enhanced algorithm performance for land cover classification from remotely sensed data using bagging and boosting
IEEE Transactions on Geoscience and Remote Sensing