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30 March 2000 Evaluation of classifier boosting
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Abstract
Boosting is a mechanism that combines a large number of weak classifiers into a single stronger classifier by taking a weighted majority vote. We show that even very simple classifiers can be combined to form a reliable classifier through boosting, even when the individual classifiers themselves are rather poor. We demonstrate these results on several interesting problems including image analysis, chemical weapon detection, and an artificial olfactory device. Some practical aspects are discussed, particularly as related to very large data sets, high dimensional data, and error improvement versus increased computation time.
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Edward J. Prokop and David J. Marchette "Evaluation of classifier boosting", Proc. SPIE 4055, Applications and Science of Computational Intelligence III, (30 March 2000); https://doi.org/10.1117/12.380603
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