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- W2123923518 abstract "Methods that create several classifiers out of one base classifier, so-called ensemble creation methods, have been proposed and successfully applied to many classification problems recently. One category of such methods is Boosting with AdaBoost being the best known procedure belonging to this category. Boosting algorithms were first developed for two-class problems, but then extended to deal with multiple classes. Yet these extensions are not always suitable for problems with a large number of classes. In this paper we introduce some novel boosting algorithms which are designed for such problems, and we test their performance in a handwritten word recognition task." @default.
- W2123923518 created "2016-06-24" @default.
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- W2123923518 date "2003-01-01" @default.
- W2123923518 modified "2023-09-25" @default.
- W2123923518 title "New Boosting Algorithms for Classification Problems with Large Number of Classes Applied to a Handwritten Word Recognition Task" @default.
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- W2123923518 doi "https://doi.org/10.1007/3-540-44938-8_33" @default.
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