Figure 1.

Schematic flow chart of sampling and evaluation processes. The original imbalanced dataset are split to training and test sets with an external stratified cross validation. The sampling process is then conducted on an internal stratified cross validation for creating a balanced training set. The classification models are built on the balanced training set and the test set from the external cross validation is classified using the obtained classification models.