Oversampling Classification of Multi-class Imbalanced Data based on Metaheuristic Algorithm

Key Points

• The aim is to explore how metaheuristic algorithms can improve oversampling methods for classifying multi-class imbalanced data.
• Application of metaheuristic algorithms for data oversampling.
• Implementation of classification techniques on generated datasets.
• Evaluation of algorithm performance through classification accuracy measurements.
• Improved classification accuracy with oversampling techniques.
• Enhanced performance metrics for multi-class data compared to traditional methods.