.. _model-surrogate-global-neural_network-max_nodes:

"""""""""
max_nodes
"""""""""


Maximum number of hidden layer nodes



**Topics**


surrogate_models


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



**Specification**

- *Alias:* nodes 

- *Arguments:* INTEGER

- *Default:* numTrainingData - 1


**Description**


Limits the maximum number of hidden layer nodes in the neural network
model.  The default is to use one less node than the number of
available training data points yielding a fully-determined linear
least squares problem.  However, reducing the number of nodes can help
reduce overfitting and more importantly, can drastically reduce
surrogate construction time when building from a large data set.
(Historically, Dakota limited the number of nodes to 100.)

The keyword ``max_nodes`` provides an upper bound.  Dakota's orthogonal
matching pursuit algorithm may further reduce the effective number of
nodes in the final model to achieve better generalization to unseen
points.