How to create a LSTM model for multivariate time dependent time series
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I want to forecast a time series using two dependent time series. How can I do this task with Matlab Deep Learning Toolbox? I used the following architecture:
Sequence Input Layer(2) LSTM Layer(100) Fully Connected Layer(1) Regression Layer
I shifted my training output by one time step and standardized the data. When I run my code I get the following error:
Invalid training data. For cell array input, responses must be a an N-by-1 array of sequences, where N is the number of sequences. …
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Venu
2024-1-11
You can refer to this example to train a multi-output LSTM network using a custom training loop:
This example shows multi-step ahead (closed loop) predictions:
This MATLAB answer can be relevant regarding your error:
Hope this helps!
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