Suppose you have a supervised learning project where it is not easy to check whether the value you predicted is correct or not. So, in this case, does it still make sense to talk about the classification error? If not, what is the possible way to check whether the predicted value is correct or not? By comparing the predicted results with the corresponding experimental results? Except this, are there other possible ways to do it?