Comparison of ensemble hybrid sampling with bagging and boosting machine learning approach for imbalanced data

Training an imbalanced dataset can cause classifiers to overfit the majority class and increase the possibility of information loss for the minority class. Moreover, accuracy may not give a clear picture of the classifier’s performance. This paper utilized decision tree (DT), support vector machine ... View More