Suppose you have picked the parameter for a model using 10-fold cross-validation (CV). Which of the following is the best way to pick a final model to use and estimate its error?

Pick any of the 10 models you built for your model; use its error estimate on the held-out data

Train a new model on the full data set, using the parameter you found; use the average CV error as its error estimate

Average all of the 10 models you got; use the average CV error as its error estimate

Average all of the 10 models you got; use the error the combined model gives on the full training set