Well, we might ask now: so the neural network has already learned from the data; how can we attest it has effectively learned? Just like in exams students are subjected to, we need to check the network response after training. But wait! Do you think it is likely a teacher would put in an exam the same questions he/she has presented in class? There is no sense in evaluating somebody's learning with examples that are already known, or a suspecting teacher would conclude the student might have memorized the content, instead of having learned it.
Okay, let's now explain this part. What we are talking about here is testing. The learning process we have covered is called training. After training a neural network, we should test whether it has really learnt. For testing, we must present to the neural network another fraction of data from the same environment it has learnt from. This is necessary because, just like the student, the...