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Response to discussion on “Improved overlap-based undersampling for imbalanced dataset classification with application to epilepsy and Parkinson’s disease.”

Vuttipittayamongkol, Pattaramon; Elyan, Eyad

Authors

Pattaramon Vuttipittayamongkol



Contributors

Alberto Fernández
Related Person

Abstract

In the paper 'Improved Overlap-Based Undersampling for Imbalanced Dataset Classification with Application to Epilepsy and Parkinson's Disease', the authors introduced two new methods that address the class overlap problem in imbalanced datasets. The methods involve identification and removal of potentially overlapped majority class instances. Extensive evaluations were carried out using 136 datasets and compared against several state-of-the-art methods. Results showed competitive performance with those methods, and statistical tests proved significant improvement in classification results. The discussion on the paper related to the behavioral analysis of class overlap and method validation was raised by Fernández. In this article, the response to the discussion is delivered. Detailed clarification and supporting evidence to answer all the points raised are provided

Citation

VUTTIPITTAYAMONGKOL, P. and ELYAN, E. 2020. Response to discussion on “Improved overlap-based undersampling for imbalanced dataset classification with application to epilepsy and Parkinson’s disease.”. International journal of neural systems [online], 30(9), article ID 2075002. Available from: https://doi.org/10.1142/s0129065720750027

Journal Article Type Letter
Acceptance Date May 25, 2020
Online Publication Date Aug 12, 2020
Publication Date Sep 30, 2020
Deposit Date Oct 19, 2020
Publicly Available Date Aug 13, 2021
Journal International Journal of Neural Systems
Print ISSN 0129-0657
Electronic ISSN 1793-6462
Publisher World Scientific Publishing
Peer Reviewed Peer Reviewed
Volume 30
Issue 9
Article Number 2075002
Item Discussed FERNÁNDEZ, A. 2020. Discussion on Vuttipittayamongkol, P. and Elyan, E., Improved overlap-based undersampling for imbalanced dataset classification with application to epilepsy and Parkinson's disease. International journal of neural systems [online], 30(
DOI https://doi.org/10.1142/s0129065720750027
Keywords Class overlap; Imbalanced data; Undersampling; Classification; Medical; Fuzzy C-means
Public URL https://rgu-repository.worktribe.com/output/969620
Related Public URLs https://rgu-repository.worktribe.com/output/940589