.. _method-adaptive_sampling-fitness_metric:

""""""""""""""
fitness_metric
""""""""""""""


(Experimental) Specify the ``fitness_metric`` used to select the next point


.. toctree::
   :hidden:
   :maxdepth: 1

   method-adaptive_sampling-fitness_metric-predicted_variance
   method-adaptive_sampling-fitness_metric-distance
   method-adaptive_sampling-fitness_metric-gradient


**Specification**

- *Alias:* None

- *Arguments:* None

- *Default:* predicted_variance


**Child Keywords:**

+-------------------------+--------------------+------------------------+---------------------------------------------+
| Required/Optional       | Description of     | Dakota Keyword         | Dakota Keyword Description                  |
|                         | Group              |                        |                                             |
+=========================+====================+========================+=============================================+
| Required (Choose One)   | Fitness Metric     | `predicted_variance`__ | Pick points with highest variance           |
|                         |                    +------------------------+---------------------------------------------+
|                         |                    | `distance`__           | Space filling metric                        |
|                         |                    +------------------------+---------------------------------------------+
|                         |                    | `gradient`__           | Fill the range space of the surrogate       |
+-------------------------+--------------------+------------------------+---------------------------------------------+

.. __: method-adaptive_sampling-fitness_metric-predicted_variance.html
__ method-adaptive_sampling-fitness_metric-distance.html
__ method-adaptive_sampling-fitness_metric-gradient.html



**Description**


``adaptive`` sampling is an experimental capability that is not ready
for production use at this time.

The user can specify the ``fitness_metric`` used to select the
next point (or points) to evaluate and add to the set.
The fitness metrics used for scoring candidate points include:

- ``predicted_variance``
- ``distance``
- ``gradient``