I trained a multiclass SVC with RBF kernel on a down-sampled (and therefore balanced) dataset. Now I want to perform grid search to find best cost and gamma.
What performance metric should I optimize for?
I have a highly imbalanced test set. There might be a factor of over 100 between the number of instances of different classes. I am classifying 3D points (car, facade, human) - so I think one could assign equal weight to all classes.