question regarding ntstool, pollution mortality example dataset

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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);
Y = net(Xs,Xi,Ai)
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

Accepted Answer

Greg Heath
Greg Heath on 2 Nov 2016
[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.

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