A bank ' s fraud detection model achieves high accuracy on its initial dataset but...

In the standard machine learning workflow, the " Validation Dataset " is specifically used for " model selection " and " hyperparameter tuning. " It serves as a bridge between training and the final test. Using the training set (Option B) for tuning would lead to overfitting. The " Testing " or " Holdout " set (Options A and C) must remain completely " unseen " until the very end to provide an unbiased final estimate of how the model will perform in the real world. According to the ISACA AAIA™ manual, maintaining this strict partitioning is critical for model integrity and preventing overly optimistic performance reports.