Comparison of Resampling Techniques for Imbalanced Datasets in Machine Learning: Application to Epileptogenic Zone Localization From Interictal Intracranial EEG Recordings in Patients With Focal Epilepsy

Comparison of Resampling Techniques for Imbalanced Datasets in Machine Learning: Application to Epileptogenic Zone Localization From Interictal Intracranial EEG Recordings in Patients With Focal Epilepsy

Aim: In neuroscience research, data are quite often characterized by an imbalanced distribution between the majority and minority classes, an issue that can limit or even worsen the prediction performance of machine learning methods. Different resampling procedures have been developed to face this p...

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Bibliographic Details
Main Authors: Giulia Varotto, Gianluca Susi, Laura Tassi, Francesca Gozzo, Silvana Franceschetti, Ferruccio Panzica
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-11-01
Series:Frontiers in Neuroinformatics
Subjects:
imbalanced dataset classification
re-sampling techniques
oversampling and undersampling
ensemble methods
network analysis
epilepsy surgery
Online Access:https://www.frontiersin.org/articles/10.3389/fninf.2021.715421/full

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