General guidelines to the use of Parameter Optimization for SVM.

pblack476pblack476 Member Posts: 83 Maven
edited November 2019 in Help
Certain learners have infinite possibilities of configuration and the task seems daunting.

So what are some guidelines on how to proceed with this step of model creation? Right now I am trying to optmize a SVM and while AutoModel gave me a starting point on that, it seems there is much more to test. How should I tackle this? What are usually effective parameters to tune in a SVM and are there recommended ranges for them?

Bear in mind that for my application I could leave a model running overnight without problems. But I am trying to understand the best I can the problem and try to avoid brute forcing it if possible.

I am on a 8750h CPU w/ 16 gb RAM

Best Answer


  • BalazsBaranyBalazsBarany Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert Posts: 955 Unicorn

    there's also the recommendation to try C in logarithmic steps from e. g. 0.0001 to 100. 

    Example with Optimize Parameters (Grid):
    Min: 0.0001      Max: 100     Steps: 6          Scale: logarithmic

    Changing C in these steps likely gives you a better information on the optimum value. But you should also try the default setting of 0, because that uses some heuristics to determine a good value. 


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