Deep learning with vector output
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I need to learn a mapping from 28x28 images into a vector of 45 floating-point numbers. This is not really classification as the numbers range between -1 and 1.
When designing a deep neural network, what output layer could I use?
Best,
Samuli Siltanen
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Answers (1)
Asvin Kumar
on 29 Aug 2019
You can use the tanhLayer to obtain output values in the range of –1 to 1.
Here’s the documentation for more information: https://www.mathworks.com/help/deeplearning/ref/nnet.cnn.layer.tanhlayer.html
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Asvin Kumar
on 30 Aug 2019
For the output layer, you can use a regressionLayer after the tanhLayer. This will produce predictions in the required range and compute the half-mean-squared-error loss.
Here's a link to the documentation: https://www.mathworks.com/help/deeplearning/ref/regressionlayer.html
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