Deep Learning Toolbox: Inputs and Outputs
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Hi everyone, I have started to transition from my own Matlab ML tool suite into the Deep Learning toolbox, and I have been unable to do the most simple of problems (a vector of elements for an input and a vector of elements for an output). Do you all know how to do this with mulitple hidden layers?
I have tried two different paths, and so far, I have failed royally.
For the 'trainNetwork', I am looking for an input layer for something that isn't a matrix in time sequence or not, but I am able to output a vector of outputs.
For 'train', I have been able to figure out how to define multiple inputs, but I am unable to output more than one value from the final layer.
This is rather dumbfounding, and I hope one of you have figured out how to fix this problem.
The image below may help you all grasp what I am trying to do, and I should note that this will be integrated into an AutoML process to define the network structure, so a GUI based answer won't work.
Matlab 19a with Deep Learning Toolbox, but I could transfer to 19b (I believe) if required.
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Sai Bhargav Avula
2019-10-23
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Hi,
If the network also has multiple inputs and outputs, then you must define the network as a function and train the network using a custom training loop. for more information.
For a detailed understanding on how to it needs to be done refer the following link.
Hope this helps
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