custom mulitiple output regression

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jaehong kim
jaehong kim am 12 Feb. 2021
Kommentiert: jaehong kim am 16 Feb. 2021
i just want mulitiple output regression custom code.
i can't find that...
i think that fullyconnectedlayer's outputsize is key for multiple output regression.
Is it correct?
ex..
layers = [
featureInputLayer(2,'Name','in')
fullyConnectedLayer(64,'Name','fc1')
tanhLayer('Name','tanh1')
fullyConnectedLayer(32,'Name','fc2')
tanhLayer('Name','tanh2')
fullyConnectedLayer(16,'Name','fc3')
tanhLayer('Name','tanh3')
fullyConnectedLayer(8,'Name','fc4')
tanhLayer('Name','tanh4')
fullyConnectedLayer(6,'Name','fc5')
];
6==outputsize
thank you for reading my question!

Antworten (1)

Raynier Suresh
Raynier Suresh am 16 Feb. 2021
Hi, For multiple regression output you can also create networks with multiple output layers. For more information on this you can refer the below link.
  1 Kommentar
jaehong kim
jaehong kim am 16 Feb. 2021
Thank you for the answer. I'll take a good reference.

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