Nested loop fuzzy logic validation

Question

Using the fuzzy toolbox in Matlab, i try to calculate the error on the validation set. First cross validation is used to split the initial training data in a training and test (validation) set. However in this validation phase I would like to obtain the error also for different parameter setting in the genfis3 function. I would like to vary the fourth input in this function from 2 to 10 and calculate the mean errors.

fismat3 = genfis3(X1,Y1,'sugeno',2);

The entire code:

 [m,~]=size(dataTrain);
    CVO = cvpartition(m,'k',10);
    err = zeros(CVO.NumTestSets,1);

    for i = 1:CVO.NumTestSets
     trIdx = CVO.training(i);
     teIdx = CVO.test(i);
     X1=Xtrain(trIdx,:);
     X2=Xtrain(teIdx,:);
     Y1=Ytrain(trIdx,:);
     Y2=Ytrain(teIdx,:);

     fismat3 = genfis3(X1,Y1,'sugeno',2);
     fismat3 = anfis([X1,Y1],fismat3);
     out1=evalfis(X2,fismat3);
     ee=Y2-out1;
     err(i)=mean(abs(ee));
end
Error32 = mean(err)

score 0 · Answer 1 · answered Jan 24 '16 at 19:17

Figured it out:

[m,~]=size(dataTrain);
CVO = cvpartition(m,'k',10);
err = zeros(CVO.NumTestSets,9);%9 denotes the amount of different parameter setting you want to validate
out = zeros(CVO.NumTestSets,1);
ee = zeros(CVO.NumTestSets,1);
for i = 1:CVO.NumTestSets %voor iedere test en training set
     trIdx = CVO.training(i); %selecteer index training data
     teIdx = CVO.test(i); %selecteer index test data
     X1=Xtrain(trIdx,:); %Creer training input variabelen
     X2=Xtrain(teIdx,:); %Creer test input variabelen
     Y1=Ytrain(trIdx,:); % Creer training output variable
     Y2=Ytrain(teIdx,:); % Creer test output variable

for j = 2:10     
     fismat3 = genfis3(X1,Y1,'sugeno',j); %creer voor iedere test en training set een andere genfis 3
     fismat3 = anfis([X1,Y1],fismat3); %optimaliseer using anfis
     out1=evalfis(X2,fismat3);          
     ee=Y2-out1;
     err(i,j-1)=mean(abs(ee));
end

end

Error = mean(err)

Nested loop fuzzy logic validation

1 Answers1