Blurb::
Surrogate model training data reuse control

Description::
Dakota's global surrogate methods rely on training data, which can
either come from evaluation of a "truth" model, which is generated by
the method specified with \ref
model-surrogate-global-dace_method_pointer, from a file of existing
training data, identified by \ref
model-surrogate-global-import_build_points_file, or both.

The \c reuse_points keyword controls the amount of training data used
in building a surrogate model, either initially, or during iterative
rebuild, as in surrogate-based optimization.  If \ref
model-surrogate-global-import_build_points_file is specified, \c
reuse_points controls how the file contents are used.  If used during
iterative rebuild, it controls what data from previous surrogate
builds is reused in building the current model.

<ul>
  <li>\c all (default for file import) - use all points in the file or
      available from previous builds
  </li>
  <li>\c region - use only the points falling in the current trust
       region (see \ref method-surrogate_based_local)
  </li>
  <li>\c none (default when no import) - ignore the
      contents of the file or previous build points, and gather new
      training data using the specified DACE method
  </li>
</ul>

Topics::	surrogate_models
Examples::
Theory::
Faq::
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