libsvm cross validation with precomputed kernel in matlab -

i trying 5 fold cross validation libsvm (matlab) using precomputed kernel, but, following error message : undefined function 'ge' input arguments of type 'struct'. because libsvm return structure instead of value in cross validation, how can solve problem, code:

load('iris.dat') data=iris(:,1:4); class=iris(:,5);  % normalize data range=repmat((max(data)-min(data)),size(data,1),1); data=(data-repmat(min(data),size(data,1),1))./range;  % train   tr_data=[data(1:5,:);data(52:56,:);data(101:105,:)]; tr_lbl=[ones(5,1);2*ones(5,1);3*ones(5,1)];   % kernel computation sigma=.8 rbfkernel = @(x,y,sigma) exp((-pdist2(x,y,'euclidean').^2)./(2*sigma^2)); ktr=[(1:15)',rbfkernel(tr_data,tr_data,sigma)]; kts=[ (1:150)',rbfkernel(data,tr_data,sigma)];  % svmptrain bestcv = 0; log2c = -1:3     cmd = ['ktr -t 4 -v 5 -c ', num2str(2^log2c)];       cv = svmtrain2(tr_lbl,tr_data, cmd);     if (cv >= bestcv)       bestcv = cv;        bestc = 2^log2c;     end  end   cmd=['-s 0 -c ', num2str(bestc), 'ktr -t 4'] model=svmtrain2(tr_lbl,tr_data,cmd)  % svm predict labels=svmpredict(class,data,model,kts) 

the function svmtrain2 using not part of standard matlab , output of function not structure. if insist use that, can calculate score data using other existing function:

[f,k] = svmeval(x_eval,varargin) 

that evaluates trained svm using outputs svmtrain2. prefer use first standard functions embedded in matlab. in standard matlab library there is:

svmstruct = svmtrain(training,group)  

that returns structure, svmstruct, containing information trained support vector machine (svm) classifier. or

svmmodel = fitcsvm(x,y)  

that returns support vector machine classifier svmmodel, trained predictors x , class labels y one- or two-class classification. , can score each prediction using:

[label,score] = predict(svmmodel,x)  

that returns class likelihood measures, i.e., either scores or posterior probabilities.