Hi,
I have a custom neural network that I trained on an old data set. I now want to retrain the same model architecture but with new data. One way could be to append the old data with the new one and shuffle, but since the data is a bit different, I want to use some basic transfer learning.
For this purpose, I need to reinitialise my netowrk with the trained weights from the old data which I sold already in a mat file. I want to know how to use these trained weights with the new network., i.e. essentially create a new network (save structure as before), initialise this netowrk with weights from the previous trained network and retrain the network with new data.
Best Regards and thanks in advance. :)
Networklayer = [...
sequenceInputLayer(featureDimension)
fullyConnectedLayer(4*numHiddenUnits1)
reluLayer
fullyConnectedLayer(4*numHiddenUnits1)
reluLayer
fullyConnectedLayer(8*numHiddenUnits1)
reluLayer
gruLayer(LSTMStateNum,'OutputMode','sequence',InputWeightsInitializer='he',RecurrentWeightsInitializer='he')
fullyConnectedLayer(8*numHiddenUnits1)
reluLayer
fullyConnectedLayer(4*numHiddenUnits1)
reluLayer
fullyConnectedLayer(numResponses)
regressionLayer];