Adaptive generation-based approaches of oversampling using different sets of base and nearest neighbor's instances

• Main Authors: Nabus, Hatem S. Y., Ali, Aida, Hassan, Shafaatunnur, Shamsuddin, Siti Mariyam, Mustapha, Ismail B., Saeed, Faisal
• Format: Article
• Language: English
• Published: Science and Information Organization 2022
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/100866/1/HatemSYNabus2022_AdaptiveGenerationbasedApproaches.pdf; http://eprints.utm.my/id/eprint/100866/; http://dx.doi.org/10.14569/IJACSA.2022.0130461

Standard classification algorithms often face a challenge of learning from imbalanced datasets. While several approaches have been employed in addressing this problem, methods that involve oversampling of minority samples remain more widely used in comparison to algorithmic modifications. Most varia...