It seems loosely reasonable but there are various things which are potentially unclear.
What exactly is a prediction, and is it deterministic or stochastic? First, if you are predicting a continuous value, you can never be "correct" - there will always be at least some very small deviation. This makes me assume that you are talking about making some discrete prediction, e.g. over some classes. In this case you would typically output a probability distribution over the different classes. If this is the case, again it's unclear what "correct" means. This makes me believe that the only way to interpret "correct" is that for any example, you deterministically output a single class, e.g. by taking the class with maximum probability, and then the prediction is considered correct when you output the correct class.
I think the biggest issue is with "all predictions correct". How do you check if all predictions are correct? Would you compute the predictions for all examples each iteration? Because that seems like the only possible way to check whether or not all predictions would be correct. More generally it's often not possible to have all predictions be correct (i.e. for an over determined problem).