# Predictive modeling techniques for in-sample rather than out-of-sample prediction?

Is it appropriate to apply predictive modeling variable selection and shrinkage techniques (for example, ridge regression or lasso) for in-sample prediction rather than out-of-sample prediction? Perhaps using 5- or 10-fold cross validation?

I think this would boil down to using a ridge regression or lasso to build an explanatory model minimizing mean squared error.