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Optimizing percentage split of CNN training/test data

조회 수: 6 (최근 30일)
Holly
Holly 2020년 8월 4일
답변: Raunak Gupta 2020년 8월 29일
I am attempting to use Bayesian optimization to find the optimal percentage split between training and validation data, when training a particular CNN.
First I define my optimizable variable
percentagechange = optimizableVariable('percentage_split',[0 1],'Type','real');
Then I use the bayesopt function to optimize my objective function
ObjFcn = makeObjFcn(lgraphlayers,ds,options);
BayesObject = bayesopt(ObjFcn,percentagechange, ...
'MaxTime',2*60*60, ...
'IsObjectiveDeterministic',false, ...
'UseParallel',false);
where I am calling my objective function that is defined as follows
function ObjFcn = makeObjFcn(lgraphlayers,ds,options)
ObjFcn = @valErrorFun;
function [valError,cons,fileName] = valErrorFun(percentagesplit)
[dsTrain,dsVal] = splitEachLabel(ds,percentagesplit,'randomize');
[trainedNetwork, info] = trainNetwork(dsTrain,lgraphlayers,options);
[predictedClass,probs] = classify(trainedNetwork,dsVal);
valError = 1 - mean(predictedClass == dsVal.Label);
fileName = num2str(valError) + ".mat";
save(fileName,'trainedNetwork','validationError','opts')
cons = [];
end
end
The problem is that using the optimizable variable in this way causes the following error:
Error using matlab.io.datastore.ImageDatastore/splitEachLabel (line 211)
Invalid parameter type. Splitting proportions must be numeric."
Error in makeObjFcn/valErrorFun
[dsTrain,dsVal] = splitEachLabel(ds,percentagesplit,'randomize');
Error in BayesianOptimization/callObjNormally (line 2560)
[Objective, ConstraintViolations, UserData] =
this.ObjectiveFcn(conditionalizeX(this, X));
Error in BayesianOptimization/callObjFcn (line 467)
= callObjNormally(this, X);
Error in BayesianOptimization/runSerial (line 1989)
ObjectiveFcnObjectiveEvaluationTime, ObjectiveNargout] =
callObjFcn(this, this.XNext);
Error in BayesianOptimization/run (line 1941)
this = runSerial(this);
Error in BayesianOptimization (line 457)
this = run(this);
Error in bayesopt (line 323)
Results = BayesianOptimization(Options);
Error in noise_hyperparameter_optimisation (line 68)
BayesObject = bayesopt(ObjFcn,percentagechange, ...
Clearly I am not permitted to put an optimizableVariable straight in to the splitEachLabel function, but I do not know how else to approach the problem. Any help would be greatly appreciated.

답변 (1개)

Raunak Gupta
Raunak Gupta 2020년 8월 29일
Hi Holly,
Since the percentagechange is accurately defined in the code for Bayesian optimization I don’t see any issue there. Only when looking into a similar example of Deep Learning using Bayesian Optimization and following syntax, I see that the percentagechange is optimizableVariable type and will through error in splitEachLabel while passing. From the syntax in the example I think
percentagechange.percentage_split
is the correct argument for splitEachLabel function. Also input to valErrorFun must be percentagechange rather than percentagesplit because no such variable (percenatagesplit) exist.
You may check the same and follow the same example syntax if there is something missing in your code.
Hope this helps!

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