I. Introduction
In recent advancements, the trends of data mining and many other machine learning applications are influenced by class imbalance problems. The processing of imbalanced data is processed relying upon two categories, such as processing the data directly and through algorithms. In data mining, the imbalance of data plays a major role and is considered one of the topmost problems to be resolved. In the case of binary problems, there is only one majority and minority class. The class imbalance problems are fraud detection, software defect prediction, cancer detection. The researchers developed a reliable technique for handling the problems that occur due to class imbalance, which affects classification performance.