How to create a simple fully connected neural network with multiple outputs?
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I need to create a fully connected neural network that can have multiple otputs.
I see RegressionNeuralNetwork is a very good solution for me, but its output size can only be 1.
Please refer me to an example.
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Answers (1)
Ashu
on 30 Nov 2022
Hey Mahmoud,
To train a network with multiple outputs, you must train the network using a custom training loop.
Example on Training and Inferencing Multiple Output Neural Network : https://www.mathworks.com/help/deeplearning/ug/train-network-with-multiple-outputs.html
To understand more about Multiple Input and Output Neural Networks : https://www.mathworks.com/help/deeplearning/ug/multiple-input-and-multiple-output-networks.html
Regards
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Ashu
on 13 Dec 2022
Edited: Ashu
on 14 Dec 2022
Hey Mahmood,
To set the weights and biases, you can use 'setwb'.
Here is a small example of creating a network with multiple outputs :
x = randn(18,141); % input data
t = randn(18,141); % ground truth label
net = feedforwardnet([ 36 36 ]);
net = train(net,x,t);
view(net)
Now to set the weights and biases -
net = setwb(net,rand(10,1));
To view the parameter values-
net.IW{1,1}
net.b{1}
To know more about 'setwb' you can refer this -
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