Using Information on Class Interrelations to Improve Classification of Multiclass Imbalanced Data: A New Resampling Algorithm

The relations between multiple imbalanced classes can be handled with a specialized approach which evaluates types of examples’ difficulty based on an analysis of the class distribution in the examples’ neighborhood, additionally exploiting information about the similarity of neighboring classes. In...

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Bibliographic Details

Published in:	International Journal of Applied Mathematics and Computer Science
Main Authors:	Janicka Małgorzata, Lango Mateusz, Stefanowski Jerzy
Format:	Article
Language:	English
Published:	Sciendo 2019-12-01
Subjects:	imbalanced data multi-class learning re-sampling data difficulty factors similarity degrees
Online Access:	https://doi.org/10.2478/amcs-2019-0057