question regarding ntstool, pollution mortality example dataset

Hello,

I have a question regarding the ntstool (neural network time series).

There is an example dataset called pollution mortality that you can load into the GUI and learn how to train a network.

The following code is also in the GUI:

[X,T] = pollution_dataset;
net = narxnet(1:2,1:2,10);
[Xs,Xi,Ai,Ts] = preparets(net,X,{},T);
net = train(net,Xs,Ts,Xi,Ai);
view(net)
Y = net(Xs,Xi,Ai)
plotresponse(Ts,Y);

The dataset has 219 input timestamps. But when you execute this code, the graph has 500 timesteps.

Could anybody tell me if code is indeed predicting observations in the future? Where does it specify how many time steps to look ahead?

Thank you

John

Answer 1

[Greg Heath]

 [X,T] = pollution_dataset;
net = narxnet(1:2,1:2,10);
[ Ic N ] = size(X) %[ 1 508]
[ Oc N ] = size(T))%[ 1 508]
x = cell2mat(X);
t = cell2mat(T);
[ I N ] = size(x) %[ 8 508]
[ O N ] = size(t))%[ 3 508]

So, where do you get 219?

 net = narxnet(1:2,1:2,10);

Therefore, the predictions are 2 timesteps ahead using 10 hidden layer nodes.