custom mulitiple output regression

2 vues (au cours des 30 derniers jours)
jaehong kim
jaehong kim le 12 Fév 2021
Commenté : jaehong kim le 16 Fév 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!

Réponses (1)

Raynier Suresh
Raynier Suresh le 16 Fév 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 commentaire
jaehong kim
jaehong kim le 16 Fév 2021
Thank you for the answer. I'll take a good reference.

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