Enhanced algorithm performance for land cover classification from remotely sensed data using bagging and boosting

IEEE Transactions on Geoscience and Remote Sensing
By: , and 

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Abstract

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.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Enhanced algorithm performance for land cover classification from remotely sensed data using bagging and boosting
Series title IEEE Transactions on Geoscience and Remote Sensing
DOI 10.1109/36.911126
Volume 39
Issue 3
Year Published 2001
Language English
Publisher IEEE
Contributing office(s) Earth Resources Observation and Science (EROS) Center
Description 3 p.
First page 693
Last page 695