How to use multiple data in LSTM?

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daemo Lee
daemo Lee on 12 Jan 2022
Commented: Pratyush Roy on 19 Jan 2022
  1. Discription said that is 'For single time step predictions, use the CPU.' I wonder how to do multi time step pridiction in Matlab.
  2. Espacially, I would like to know about the way to use multi training data set for LSTM, not single training data set like this example.
That example used a double data(1xN), but I hope to enter multiple(M) double data(like MxN).
Please let me know some idea or give your knowledge.

Accepted Answer

Pratyush Roy
Pratyush Roy on 17 Jan 2022
Hi Daerno.
The example mentioned in the question is used for finding temporal relation between 1-D input and 1 dimensional output. As mentioned in the code:
numFeatures = 1;
numResponses = 1;
numHiddenUnits = 200;
layers = [ ...
sequenceInputLayer(numFeatures)
lstmLayer(numHiddenUnits)
fullyConnectedLayer(numResponses)
regressionLayer];
The number of features is 1. Hence the data passed as input is 1-dimensional in nature.
In general, LSTMs are built to work for multi-dimensional data. We can change the numFeatures and numResponses value to map one single/multi-dimensional vector to another single/multi-dimensional vector. This doc link captures a example involving multi-dimensional vectors.
Hope this helps!
  2 Comments
Pratyush Roy
Pratyush Roy on 19 Jan 2022
Hi Daemo,
Since you have multiple datasets, you can train multiple LSTMs in parallel. Please refer to the doc link below for more details:
Hope this helps!

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