Imagine a scenario in which a model works perfectly well with the data it was trained on, but provides incorrect predictions when it meets new, unfamiliar data. On the other hand, in certain cases, it struggles to grasp the intricacies of the data and thus fails to provide an accurate prediction.
Striking a balance between accuracy and the ability to make predictions beyond the training…
