My question is about Neural Network Training. I already searched about this but, there is no good explanation about it.
So for the first one, how to calculate mean square error? (I know this is silly, but I really don't get it)
second: When Neural Network do its training , we inputted a Training Set which consists of many pairs(Input and its desired output). Now when should we calculate the mean square error? does it when we already take all pairs? or does we calculate it for each pair?
if it is for each pair, then there is possibility when the error reaches the minimum desired error before all pairs inside Training set taken.
third: does epoch value increase for one loop of training set? or does it increase when each pairs(input and desired output) taken?(I know this is another silliness but please bear with it)
thank you very much