Early stopping configuration: Specifies the various configuration options for running training with early stopping.
Users need to specify the following:
(a) EarlyStoppingModelSaver: How models will be saved (to disk, to memory, etc) (Default: in memory)
(b) Termination conditions: at least one termination condition must be specified
(i) Iteration termination conditions: calculated once for each minibatch. For example, maxTime or invalid (NaN/infinite) scores
(ii) Epoch termination conditions: calculated once per epoch. For example, maxEpochs or no improvement for N epochs
(c) Score calculator: what score should be calculated at every epoch? (For example: test set loss or test set accuracy)
(d) How frequently (ever N epochs) should scores be calculated? (Default: every epoch)