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

Chan, J. C. -W.; Huang, C.; DeFries, R.

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.

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Article

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70023633

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Chan, J. C. -W.; Huang, C.; DeFries, R.

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695

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English

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IEEE Transactions on Geoscience and Remote Sensing

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Enhanced algorithm performance for land cover classification from remotely sensed data using bagging and boosting; 2001; Article; Journal; IEEE Transactions on Geoscience and Remote Sensing; Chan, J. C. -W.; Huang, C.; DeFries, R.