Effacer les filtres
Effacer les filtres

Bayesian Hyperparameter for Anfis

4 vues (au cours des 30 derniers jours)
Raghu
Raghu le 26 Juin 2021
Modifié(e) : Raghu le 29 Juin 2021
Hello,
I tried developing codes for ANFIS for 2 inputs and 1 output using example provided by the Matlab. I would like to optimise it using the bayesian optimisation for hyperparameter tuning such as membership function and parameter tuning. Can someone please help me with that because the code is not working?
This is my code for the ANFIS:
Daten = rand(100, 3);
Daten(:,3) = Daten(:,1) + Daten(:,2) + .1*randn(100, 1);
[m,n] = size(Daten) ;
[m,n] = size(y) ;
% Split into train and test
P = 0.7 ;
Training = y(1:round(P*m),:) ;
Testing = y(round(P*m)+1:end,:);
XTrain = Training(:,1:n-1);
YTrain = Training(:,n);
XTest = Testing(:,1:n-1);
YTest = Testing(:,n);
%%
cv = cvpartition(numel(YTrain), 'Holdout', 1/3);
% Define hyperparameters to optimize
vars = [optimizableVariable('MF', [1,20], 'Type', 'integer');
optimizableVariable('EN', [1,100], 'Type', 'integer')];
% Optimize
minfn = @(vars)kfoldLoss(XTrain', YTrain', cv, vars.MF, vars.EN);
results = bayesopt(minfn, vars,'IsObjectiveDeterministic', false,...
'AcquisitionFunctionName', 'expected-improvement-plus');
vars = bestPoint(results);
% ANFIS model
a= Training % training data
x= [a(:,1),a(:,2)]; % input for anfis
opt = anfisOptions('InitialFIS',vars.MF,'EpochNumber',vars.EN);
opt.DisplayErrorValues = 0;
opt.DisplayStepSize = 0;
fis = anfis(y,opt);
anfisOutput= evalfis(fis,x);
z= anfisOutput;

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