"Greg Heath" <firstname.lastname@example.org> wrote in message > > If my understand is right, I really wonder about the following: > > 1. with only weight set, I think we have only mse for network in train. > ? > I do not understand the statement.
> Even it not change in predict on a fix range of time by 1-step( apply weight for new input and calculate mse again). > > I don't understand. >
Assume I follow by your way, I found the best Delay and Hidden for network. With delay and hidden,e.g delay = 10, hidden =4, we will found only weight set for network(althought we have many nets but just to change the order of weight). If it right, it lead to network just give only result for 1 pattern input. And same thing, we just only have 1 mse result for network to apply for some pattern input set( i just apply and calculate again mse not retrain). But when i run code and test on fix new pattern input set. For each run, I get a new mse to apply. I try to set a fix intialize weight, I see mse not change. So what the reason make msse change if we just have only weight set for network?
Please do not be angry if I say something wrong. I'm just trying to understand right. I want to create a network and test it on the new input sets, then measure error of network, check trend(up or down) of predict value to corresponding with real value. Please help me. I really need your help. Thank you so much Phuong