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can someone explain me the batch attribute role? what can I do with it and maybe with an example?
When you use cross-validation RM separates the samples into K partitions at random (or in a stratified way). If you want to have full control of how the observations are assigned to the different partitions you use batch. This is going to be a column with numbers from 1 to K indicating the partition to which each observation belongs.
I've used batch cross-validation when I want to compare the results from Rapidminer to the results of other programs.
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