[SOLVED] Select Hyperparameters of SVM in cross-validation?
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
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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Got it, thanks!
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.