Azzera filtri
Azzera filtri

using LSTM nets for classification with multiple outputs

8 visualizzazioni (ultimi 30 giorni)
I'm using LSTM nets for classification.
I would like to have 3 outputs of 3 values (-1 0 +1)
Apparently the Matlab framework for that nets accepts only one output. In this case it should have 27 values (3^3), but it adds complications.
Any suggestion?
Giuseppe Menga

Risposte (1)

Shreeya
Shreeya il 12 Dic 2023
To build an LSTM based neural netowkr with three prediction classes, create a layer array containing a sequence input layer, an LSTM layer, a fully connected layer, a softmax layer, and a classification output layer. Further, set the size of the sequence input layer to the number of features of the input data and the size of the fully connected layer to the number of prediction classes classes.
Refer to the link below for more details:
  1 Commento
Giuseppe Menga
Giuseppe Menga il 12 Dic 2023
Thanks for the answer, I saw the link you indicated.
I didn't understain the difference between the two examples of classification:
To create an LSTM network for sequence-to-label classification
lstmLayer(numHiddenUnits,'OutputMode','last')
To create an LSTM network for sequence-to-sequence classification
lstmLayer(numHiddenUnits,'OutputMode','sequence').
I used sequence-to-label classification, but to apply the classification in real time I will test the other.
But you didn't answer to my basic question:
using three outputs, each with three levels of classification, or transforming them in only one output with twentyseven levels of classiicaton.
I suspect that I have to transform the problem with only one output with twentyseven levels, as I haven't found any other example.
Have you some observation?
Giuseppe

Accedi per commentare.

Prodotti


Release

R2023b

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by