How to handle very short sequences in LSTM Network
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Hello Matlab Community,
I am using MATLAB 2018b I am trying to apply the sequence to sequence regression network on a dataset with very short sequences.
I basically followed the 'Sequence-to-Sequence Regression Using Deep Learning' tutorial which is given by MATLAB.
When I apply this tutorial to my dataset it only returns NaN as a prediction.
And the graph also suggests that it stops calculating after some iterations.
this is the verbose output:
|=========================================================================|
| Epoch | Iteration | Time Elapsed | Mini-batch | Mini-batch | Base Learning |
| | | (hh:mm:ss) | RMSE | Loss | Rate |
|======================================================================|
| 1 | 1 | 00:00:01 | 65.11 | 2119.5 | 0.0100 |
| 5 | 50 | 00:00:04 | NaN | NaN | 0.0100 |
| 9 | 100 | 00:00:06 | NaN | NaN | 0.0100 |
| 13 | 150 | 00:00:07 | NaN | NaN | 0.0100 |
| 17 | 200 | 00:00:09 | NaN | NaN | 0.0100 |
| 20 | 240 | 00:00:15 | NaN | NaN | 0.0100 |
|=======================================================================|
I'd be super happy if anyone had some suggestions to solve that issue!
I already tried looping over the single short iterations - which let to endlessly poping up windows and a server crash.
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