Deepakindresh N, Gauthum J, Jeffrin Harris, Harshavardhan J and Shivaditya Shivganesh, Vellore Institute of Technology, India

The paper is an analysis of class imbalance problems from various domains such as the medical field, sentiment analysis, software de-fects, water portability, and relationship status of students and summarizes the performance of data resampling techniques such as random undersampling and oversampling. Synthetic minority oversampling techniques combined with the power of ensemble methods such as bagging, boosting, and hybrid techniques are generally used to solve the class imbalance problem.

Machine Learning, Class Imbalance, Multi Domain Analysis.