Hi,
My question might be a little general.

I have a number of values to select for the complexity parameters in some 
classifier, e.g. the C and gamma in SVM with RBF kernel. The selection is based 
on which values give the smallest cross validation error.

I wonder if the randomized splitting of the available dataset into folds is 
done only once for all those choices for the parameter values, or once for each 
choice? And why?

Thanks and regards!

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