As could cross validation in a neural network NarX?

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FRANCISCO
FRANCISCO 2013-2-14
I would like to know how to raise the cross-validation for NarX neural network, in this way, not destroy correlations. I have a set of 1136 data and 1136 data input targets.
thank you very much

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Shashank Prasanna
Shashank Prasanna 2013-2-14
You may want to use DIVIDEBLOCK instead of the default dividerand. DIVIDEBLOCK will maintain correlation since it doesn't shuffle the data but takes block of it for crossvalidation:
http://www.mathworks.com/help/nnet/ug/improving-generalization.html
http://www.mathworks.com/help/nnet/ref/divideblock.html

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