MATLAB: Avoid training certain neurons

backpropagationdeep learningDeep Learning Toolbox

Using the Deep Learning Toolbox, I wish to construct a simple feed-forward network for a simulation, however assume I have already trained one of the hidden neurons (out of several) with the correct weights and biases and I don't want them to change during training. How can I make this single specific neuron be "constant" and not get retrained with new wights and biases while the rest of the network is being trained?

Best Answer

There is an option to keep specific layers' learning rates low so you can fix them as they are.
for example
fullyConnectedLayer(<outputsize>, 'WeightLearnRateFactor', 0, 'BiasLearnRateFactor', 0)
This way, you would multiply zero to the global learning rate, which is set via trainingOptions function, and thus the learning rates of the weights in the fully-connected-layer are set as zero.
Check this out - this may help you out too.
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