megmeg Member Posts: 1 Contributor I
edited November 2018 in Help
I have some questions:
1. how can i use cross-validation in rapid miner? is it possible in rapid miner?
2. which fitness function use rapid miner to learn (MSE??)?

Kind regards


sorry for my english


  • landland RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 2,531 Unicorn
    Hi Meg,
    there is an operator that performs the crossvalidation available, of course. The operator is called "XValidation", which might somehow be missleading. For learning how this operator can be used, you should take a look at the online tutorial, explaining some of the sample processes, which come with rapid miner. At least one of them explains the XValidation in detail.
    The second question is harder to answer, since it depends on what you are doing. For example Linear Regression and SVM do use different fitnessfunctions. Both fittnessfunctions are resulting from the algorithms itself and do not depend on rapid miner. If you perform a parameter optimization for tuning learning algorithms parameters, you might select out of a large list of available fittness functions. For example absolute_error or MSE or something like that.

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