Hi Hussein, What do you mean by "type of cross-validation" in neural networks? The Start/End group nodes support cross validation for any model. For a quick example, take a look at page 7 of this paper (http://support.sas.com/resources/papers/proceedings10/123-2010.pdf)... I can't remember top of my head if you have that option in EM 6.2. If your EM version does not have cross validation option for the Start groups, I suggest go back to the basics. When I read the wikipedia definition of k-fold validation, it sounds like something easy to do in EM. Just an idea, use several Sample nodes, add the same model node to all of them, and use an Ensemble node to combine the posterior predicted probabilities. I have not ran this, but that would be my first try. Please let me know if this worked OK. Thanks! Miguel
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