DTO-SMOTE: Delaunay Tessellation Oversampling for Imbalanced Data Sets

One of the significant challenges in machine learning is the classification of imbalanced data. In many situations, standard classifiers cannot learn how to distinguish minority class examples from the others. Since many real problems are unbalanced, this problem has become very relevant and deeply...

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Bibliographic Details

Published in:	Information
Main Authors:	Alexandre M. de Carvalho, Ronaldo C. Prati
Format:	Article
Language:	English
Published:	MDPI AG 2020-11-01
Subjects:	machine learning SMOTE oversampling DTO-SMOTE imbalanced data
Online Access:	https://www.mdpi.com/2078-2489/11/12/557