I have 5379 observations in a data set. Its a classification problem where the no. of bad's is 25 and the no. of goods is 5354. I want to do a 5 fold cross validation in which 5 classes will consist of 5 bad's respectively and the no. of goods distributed equally. How do i make the split?!!!
There are few methods to handle such imbalanced data. Stratified sampling will not help you in your case, because of large variation. Best is to augment some data using SMOTE. It use graph network, to augment the data in smart way. Give it a try.
Another you can try sampling technique, by considering over and under sampling technique. Using oversampling methods, we can repeat the sample with less instances, whereas with under-sampling, we loss some data of many instances. For more, you can refer