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Cross-Validation and Grid-Search Optimization
I was wondering if I could get some clarification on the correct nesting and setting of parameters to use grid-search optimization within n-fold cross-validation. I assume the optimization operator is nested within cross-validation to select parameters as described in this article: https://rapidminer.com/learn-right-way-validate-models-part-4-accidental-contamination/
How is the set parameter operator used to correctly set the parameter in question for the model to be applied to the data after optimization has been performed?
Any clarification on these processes would be helpful,