Which DLPy parameter enables early stopping during model.fit() training?
Select an answer to reveal the explanation.
Short Explanation
You enable early stopping in SAS DLPy by configuring a solver object with early stopping parameters and passing it to model.fit(). That solver monitors validation performance and stops training when improvement stops for the specified number of epochs.
Full Explanation
The EarlyStopping-configured solver object passed to model.fit() is correct because SAS DLPy supports early stopping by configuring a solver object with early stopping parameters, then passing it to model.fit(). It monitors validation performance and stops training when improvement ceases for a specified number of epochs. The stop_threshold= in model.fit() option is not a standard DLPy parameter. The patience= combined with n_threads= option conflates unrelated concepts. The max_epochs= option is wrong because DLPy requires explicit early stopping configuration.