Cascading Regularized Classifiers
Among the various methods to combine classifiers, Boosting was originally thought as an stratagem to cascade pairs of classifiers through their disagreement. I recover the same idea from the work of Niyogi et al. to show how to loosen the requirement of weak learnability, central to Boosting, and in...
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| Language: | en_US |
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2005
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| Online Access: | http://hdl.handle.net/1721.1/30463 |