Working with LSTM and Bayes Optimization

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CHRISTOPHER MILLAR
CHRISTOPHER MILLAR el 25 de Feb. de 2020
Comentada: CHRISTOPHER MILLAR el 5 de Oct. de 2021
I am trying to use bayesoptimization to tune the parameters
optimvars = [
optimizableVariable('InitialLearnRate',[1e-2 1],'Transform','log')
optimizableVariable('L2Regularization',[1e-10 1e-2],'Transform','log')];
layers = [ ...
sequenceInputLayer(inputSize,'Normalization','zscore')
bilstmLayer(numHiddenUnits,'OutputMode','last')
fullyConnectedLayer(numClasses)
softmaxLayer
classificationLayer];
maxEpochs =25;
options = trainingOptions('adam',...
'ExecutionEnvironment','cpu',...
'GradientThreshold',1,...
'MaxEpochs',maxEpochs,...
'MiniBatchSize',miniBatchSize, ...
'SequenceLength', 'longest', ...
'Shuffle','every-epoch', ...
'Verbose', 1, ...
'InitialLearnRate',optimvars.InitialLearnRate,...
'L2Regularization',optimvars.L2Regularization,...
'Plots','training-progress');
objFcn = makeObj(Xtrain,YTrain);
bayesObj = bayesopt(objFcn,optimvars, ...
'MaxTime', 14*60*60, ...
'IsObjectiveDeterministic',false,...
'UseParallel',false);
Where am i going wrong as i get the following error:
Unrecognized method, property, or field 'InitialLearnRate' for class 'optimizableVariable'.
Error in AllVsIndx (line 236)
'InitialLearnRate',optimvars.InitialLearnRate,...
The documentation regarding bayesian optimization is very vague especially when it comes to implementation with LSTM networks
Any help would be appreciated
Thanks

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Jorge Calvo
Jorge Calvo el 27 de Mayo de 2021
If you have R2020b or later, you can use the Experiment Manager app to run Bayesian optimization to determine the best combination of hyperparameters. For more information, see https://www.mathworks.com/help/deeplearning/ug/experiment-using-bayesian-optimization.html.
  1 comentario
CHRISTOPHER MILLAR
CHRISTOPHER MILLAR el 27 de Mayo de 2021
Thanks Jorge
I have just installed R2021a on my machine and will take advantage of this new app

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Más respuestas (2)

Don Mathis
Don Mathis el 25 de Feb. de 2020

Jorge Calvo
Jorge Calvo el 5 de Oct. de 2021
I thought you would like to know that, in R2021b, we are included an example for training long short-term memory (LSTM) networks using Bayesian optimization in Experiment Manager:
I hope you find it helpful!
  1 comentario
CHRISTOPHER MILLAR
CHRISTOPHER MILLAR el 5 de Oct. de 2021
Hi jorge,
Yes I have been using it and it makes the optimization process very easy to use.
Thanks for updating the thread with this information.
Regards
Chris

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