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
``convergence_tolerance`` is achieved, or ``max_function_evaluations`` or
``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 ``dace_method_pointer``.
See :dakkw:`method-sampling-refinement_samples` for more information.
Topics::
surrogate_models
Examples::

Theory::

Faq::

See_Also::
