I'm currently using early stopping in my work to prevent over fitting. Specifically those taken form Early Stopping But When?.
I'm now wanting to compare to other classification algorithms where it appears that 10 fold cross validation is widely used.
However I'm confused about whether cross validation is a method for preventing over fitting or selecting good parameters. (or maybe this is one and the same?). I'm also confused whether early stopping methods and cross validation can be used in place of one another or in combination.
So the question is: what is the relationship between early stopping and cross validation?