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

Two ensemble methods, bagging and boosting, were investigated for improving algorithm performance. The authors' results confirmed the theoretical explanation of L. Breiman (1996) that bagging improves unstable, but not stable, learning algorithms. While boosting enhanced accuracy of a weak lear...

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Bibliographic Details
Published in:	IEEE transactions on geoscience and remote sensing Vol. 39; no. 3; pp. 693 - 695
Main Authors:	Jonathan Cheung-Wai Chan, Chengquan Huang, DeFries, R.
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01.03.2001 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Aggregates Applied geophysics Bagging Boosting Earth sciences Earth, ocean, space Exact sciences and technology Geography Image resolution Internal geophysics MODIS Pressing Radiometry Sampling methods Voting algorithms algorithm performance radiometry accuracy remote sensing classification high resolution
ISSN:	0196-2892, 1558-0644
Online Access:	Get full text
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