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custom mulitiple output regression

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jaehong kim
jaehong kim on 12 Feb 2021
Commented: jaehong kim on 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!

Answers (1)

Raynier Suresh
Raynier Suresh on 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 Comment
jaehong kim
jaehong kim on 16 Feb 2021
Thank you for the answer. I'll take a good reference.

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