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Dynamic selection of the best base classifier in one versus one
(Elsevier, 2015-05-19)
Class binarization strategies decompose the original multi-class problem into several binary sub-problems. One versus One (OVO) is one of the most popular class binarization techniques, which considers every pair of classes ...
NewOneVersusOneAll method: NOV@
(Elsevier, 2014-04-19)
Binarization strategies decompose the original multi-class dataset into multiple two-class subsets, learning a different binary model for each new
subset. One-vs-All (OVA) and One-vs-One (OVO) are two of the most well-known ...
Classifier Subset Selection to construct multi-classifiers by means of estimation of distribution algorithms
(Elsevier, 2015-01-24)
This paper proposes a novel approach to select the individual classifiers to take part in a Multiple-Classifier System. Individual classifier selection is a key step in the development of multi-classifiers. Several works ...