custom mulitiple output regression
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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!
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Antworten (1)
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.
Siehe auch
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