custom mulitiple output regression

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jaehong kim
jaehong kim 2021-2-12
评论： jaehong kim 2021-2-16
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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回答（1 个）

Raynier Suresh
Raynier Suresh 2021-2-16
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.
https://www.mathworks.com/help/deeplearning/ug/train-network-with-multiple-outputs.html#responsive_offcanvas

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