This cross-validation would essentially conduct automated experiments on subsets of the training data and find a good λ value. Then this λ would be used to learn a regularized model on all the training data. This has become the standard procedure for building numerical models that give a good balance between data fit and model complexity. This general approach to optimizing the parameter values of a data mining procedure is known as grid search.
grid search
