Blurb::
Experimental auto-refinement of surrogate model

Description::
(Experimental option) Automatically refine the surrogate model until
desired cross-validation quality is achieved. Refinement is accomplished
by iteratively adding more data to the training set until the cross-validation
\c convergence_tolerance is achieved, or \c max_function_evaluations or 
\c max_iterations is exceeded.

The amount of new training data that is incorporated each iteration is specified
in the DACE method that is referred to by the model's \c dace_method_pointer.
See \ref method-sampling-refinement_samples for more information.

Topics::
surrogate_models
Examples::

Theory::
Faq::
See_Also::
