I want to use LIBSVM in MatLab to do some multi-class classification. I have read that LIBSVM use One vs. One by default when provided with multiple labels, and I am fine with it.
My question is about the parameter search and the model validation. When doing a 2-class validation to find the parameters C and gamma (when using RBF as kernel), I would use the built-in cross validation to find the best (C,gamma)-pair, using a simple grid search. I have read the LIBSVM documentation but I have no idea how validation works for multiclass SVM.
Does the built-in option returns the multi-class accuracy? How can I provide the best parameters to each of the OvO models it will automaticaly built?
