[D] How can you uncover outliers using prediction models?
Lets imagine you are looking at library of books and you want to see which books are longer overdue than expected (with characteristics such as word count, genre, author), one plausible method would be to split all books into two unique sets. The first is used to train the model and the second is used to predict the expected time overdue. And then these sets are swapped around and the other side’s over or underdueness is predicted. Does this method have a name? And is there any other method available to do something similar. (Another example would be to predict under and over pay based on employee characteristics_)