Hello,
I'm wondering what happens if I have more input steps of a sequence than hidden units of LSTM blocks.
For example below: What happens if I have 5 timeseries inputs but my network has only 2 hidenn LSTM blocks. How can the system learn?
Is it just feeding inside the first two timeseries inputs? What happens with the last three?
Code example:
numfeatures
layers = [ ...
sequenceInputLayer(numfeatures)
lstmLayer(2,'OutputMode','last')
fullyConnectedLayer(1)
regressionLayer];
Can someone help?
Thanks.
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