Answer (1 of 4): It really depends on your "goal" and your dataset. Classification Accuracy (or misclassification error) makes sense if your class labels are uniformly distributed. Even better, you can compute the ROC area under the curve (even for multi-class sytems), e.g., there's a nice tutori...