Figure 2.

Our evaluation process for the performance of ML and DL algorithms (each step of 5-CV). The collected data were split into 80% for training and 20% for testing. The sampling methods were either applied only to the training data to balance the distribution of class labels or not, after which the models were fitted to the preprocessed data. We then tested them using the test data to evaluate predictive performance.