Neural Network Regression Problem with multiple Outputs
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Hello everyone, I am now having a 1000 images, which have 10 continous attributes. My goal is to predict these 10 attributes values when I feed it a new image, after training.
So I think it is like a regression problem and I expect there will be 10 regression output layers in respond to these 10 attributes. How can i achieve this with Matlab? I think trainNetwork doesnt work. It is only applicable for non-multi-output lgraph.
Then I look at this:Train Network with Multiple Outputs https://www.mathworks.com/help/deeplearning/examples/train-network-with-multiple-outputs.html
Is that right direction? If not, can you point me?
I dont really know what parameters and state are.
I would be gladful if you leave a comment.
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回答 (1 件)
Srivardhan Gadila
2020 年 3 月 14 日
The last two layers of your network architecture must be a fullyConnectedLayer with outputSize 10 followed by regressionLayer
layers = [ ...
fullyConnectedLayer(10)
regressionLayer];
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