I have performed 10 fold cross validation for performance estimation on a keras model. I now want to train a final neural network using ALL data for the FINAL model that will be deployed.
Given that this is the recommendation (to generate final model on all data), and I now no longer have any holdout data, conceptually, could I also average epochs taken to train during cross validation over the 10 folds to determine an epoch range that will not result in overfitting? or should i simply run 'x' epochs, overshoot and then simply determine the plateu?
is there a general rule here?
or... should I still have a validation split during training but no test set. This option makes no sense to me as this is exactly what cross validation was for.