#multiple-testing

You evaluate model $f_1$ on the test set, then design $f_2$ using what you saw and evaluate it on the same test set. Because $f_2$ was chosen after information from the test set reached you, the set is no longer a true test set; this problem is called overfitting. Evaluating many models on one test set also raises the problem of multiple hypothesis testing, that is, of false .