I have another confusion
Is there any thumb rule or relation between number of neurons in hidden layer and input variables? suppose, I have a data set with 10 input variables. By hit and trial method, how many neurons maximum can I try? I understand that as number of neurons increase, correlation and mse also improves. But at same time, network gets overtrained. How can I be sure that I am not overtraining the network?