General guidelines to the use of Parameter Optimization for SVM.
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