Muhammad Azeem Akbar

SMOTE extensions for abnormal minority instances in imbalanced time series classification

Abstract Class imbalance remains a significant challenge in time series classification, especially when the minority samples include abnormal or outlier instances. This study proposes four extensions of the Synthetic Minority Oversampling Technique (SMOTE): Distance Extended SMOT...