C. Huang R. DeFries J.C.-W. Chan 2001 Two ensemble methods, bagging and boosting, were investigated for improving algorithm performance. Our results confirmed the theoretical explanation [1] 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. application/pdf 10.1109/36.911126 en IEEE Enhanced algorithm performance for land cover classification from remotely sensed data using bagging and boosting article