I am currently working on data imbalance using SMOTE for binary and other algorithms for the multi-class problem.
I have the idea how to create the synthetic example to bring noticeable accuracy on a given dataset.
I want to go into deep and understand how a classifier, especially SVM handle the data with the synthetic example to classify more accurately. It would also helpful to know for other techniques like boosting algorithms, random forest etc.
Any kind of guidance on above question will be very much helpful.
I have already asked this question on StackExchange here but didn't get any answer.