How to Test Overfitting When There is not Enough Data for a Testing Set?

A good neural network has to produce precise results not only when dealing with training data but also when it is used for cases which has not been presented during a process of training. It means that in order to test a neural network’s performance you have to possess more examples than you use to train it. But what should you do if you have even a problem with gathering enough data for training? Where can you find new examples? This problem, in one of two possible kinds of overfitting, can be solved by using a method which will be presented in this article.