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[SOLVED] Select Hyperparameters of SVM in cross-validation?

johnny5550822johnny5550822 Member Posts: 12 Contributor II
edited October 2019 in Help
Hi,

I want to clarify one thing about what rapidminer exactly is doing. When I put a SVM module inside cross-validation (e.g. 10-fold), will the SVM algoirithm optimize the hyperparameters (e.g. C) based on cross-validation result?

If so, what about if I don't have validation, and basically just give data to SVM module, how does rapidminer get the hyperparameters value?

Thanks,
Johnny

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    frasfras Member Posts: 93 Contributor II
    Cross Validation (CV) does not optimize at all. Doing a 10-fold or 5-fold CV ensures only to get performance parameters you can trust.
    If you want to optimize e.g. "C" you have to put the CV into the "Optimize Parameters" Operator that performs a training/validating with
    all selected values of C. Take a look into the example process delivered together with the operators help.
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    johnny5550822johnny5550822 Member Posts: 12 Contributor II
    Got it, thanks!
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