Hi Alexis. Specifying a value for 'Prior' will affect the training process for the SVM, which will then make a difference in how it predicts for the test set. In any case, the values for 'Prior' shouldn't necessarily be the prior probabilities of your test set, but rather, the realistic class prior probabilities.
It can be problematic when the real prior probabilities differ significantly from the prior probabilities in your training set. If your training set is representative of the population, then you shouldn't have to provide anything for 'Prior'.
This is a more general problem known as class imbalance, or imbalanced data sets. You can see the Answers post below for previous suggestions on how to account for this problem: