K-means-SMOTE for handling class imbalance in the classification of diabetes with C4.5, SVM, and naive Bayes

The occurrence of imbalanced class in a dataset causes the classification results to tend to the class with the largest amount of data (majority class). A sampling method is needed to balance the minority class (positive class) so that the class distribution becomes balanced and leading to better cl... View More