Out-of-fold prediction

Also written: oof, out-of-fold

A prediction for a row made by a model that was not trained on that row, because the row was in the fold held out during cross-validation. These predictions give an honest estimate of how the model behaves on unseen data, so they can be used to choose a threshold without using the test set.