I’m working on a system that can optimize parameters of SVM (LIBSVM toolbox) and best features (inputs) together. My optimization techniques is harmony search or genetic algorithm. I normalized data before insert it to system ( Maxmin or whitening) so as you know I must set
-g gamma : set gamma in kernel function
-c cost : set the parameter C of C-SVC, epsilon-SVR, and nu-SVR
I have a binary classification problem with financial database. Besides it sometimes I’m using dimension reduction techniques like “PCA” and other techniques.
So what is your proposed searching intervals for gamma and cost parameters?
Second question : What other parameters of LIBSVM do you think i should optimize with my optimization technique?
Thanks.
PS. My kernel function is "RBF"