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LSTM Sequence to One Regression

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juan pedrosa
juan pedrosa on 26 Oct 2019
Commented: Michael Hesse on 11 May 2021 at 7:11
I'm trying to train a LSTM network for Sequence to one regression, but I'm having problems with my dataset, although I'm using the definition given by Mathworks here
My train set is a N by 1 cell array where N=2,396,493 and each sequence is an 8 by 22 double.
My response set is a N by R matrix where N=2,396,493 and R = 8
I'm using a mini batch size of 300 and when I try to train the network this is the error output:
Error using trainNetwork (line 165)
Unable to perform assignment because the size of the left side is 8-by-300 and the size of the right side is 1-by-300.
I've tried different setups for the response set by transposing it or make it an N by 1 cell array to no results. I did trained a Sequence to sequence network but I think I'll get better results with a Sequence to one network, any advices please?
It seems that the minibatch size is the problem (bug?), if the minibatch size is set to 1 then the training begins without issues.
Thank you for your time.
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juan pedrosa
juan pedrosa on 17 Sep 2020
it has been almost a year and the error still prevails, I've lost hope in matlab, I'm moving to tensorflow.

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Answers (2)

shubhan vaishnav
shubhan vaishnav on 11 Feb 2021
send the code
  1 Comment
juan pedrosa
juan pedrosa on 11 Feb 2021
No need thank you! Tensorflow is awesome!

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Josephine Morgenroth
Josephine Morgenroth on 19 Apr 2021 at 15:36
I'm having the same issue - trying to the use sequence-to-one framework using OutpuMode = 'last' with no success. I have a time series dataset with 10 features to predict 3 targets, with a total of 30 sequence/target rows. The code runs fine, but the LSTM predicts the same value for all the sequences! Has anyone seen an example where this structure was successfully used in MATLAB?
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Michael Hesse
Michael Hesse on 11 May 2021 at 7:11
hi josephine, i'm working on the same problem. in the last couple days i figured out that the
padding option does have a huge impact on the training and prediction performance.
in particular for my case: the setting 'SequencePaddingDirection', 'left', ... has brought the breakthrough.
hope it helps, michael

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