Working with LSTM and Bayes Optimization
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CHRISTOPHER MILLAR
le 25 Fév 2020
Commenté : CHRISTOPHER MILLAR
le 5 Oct 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
le 27 Mai 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.
Plus de réponses (2)
Don Mathis
le 25 Fév 2020
You might find this similar example useful: https://www.mathworks.com/matlabcentral/answers/457788-lstm-time-series-hyperparameter-optimization-using-bayesian-optimization?s_tid=answers_rc1-2_p2_MLT
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Jorge Calvo
le 5 Oct 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!
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