• Step 3: All N base model predictions from step 2 for folds 0-7 are concatenated (stacked) to construct ensemble features. The Model-Based Ensemble is then trained with these ensemble features as input and the true labels as output for folds 0-7. For the Max Vote Ensemble, no training is needed as the output is the maximum of the ensemble features.