Instance reduction for one-class classification

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Instance reduction for one-class classification

Instance reduction techniques are data preprocessing methods originally developed to enhance the nearest neighbor rule for standard classification. They reduce the training data by selecting or generating representative examples of a given problem. These algorithms have been designed and widely anal...

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Bibliographic Details
Main Authors:	Krawczyk, Bartosz, Triguero, Isaac, García, Salvador, Woźniak, Michał, Herrera, Francisco
Format:	Article
Published:	Springer 2018
Subjects:	Machine learning ; One-class classification ; Instance reduction ; Training set selection ; Evolutionary computing
Online Access:	https://eprints.nottingham.ac.uk/52077/

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