multi-class support vector machine classification -

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i try run own svm-code using 1 against 1 have error in selected function best (c,sigma) , error in plot function ,i hope give me hand,and code

clear clc close %load data load dataset load spacies [~,~,group] = unique(spacies); data=dataset(1:12,1:19); xdata=zscore(data); %group=spacies(1:end,1); p=0.5; [train,test]=crossvalind('holdout',group,p); trainingsample=xdata(train,:); traininglabel=group(train,1); testingsample=xdata(test,:); testinglabel=group(test,1); numclass=max(group); i=1:numclass     j=i+1:numclass         inij=(traininglabel==i)|(traininglabel==j);         trainingsampleij=trainingsample(inij,:);         traininglabelij=traininglabel(inij,:);         %%k-fold using training data         numfold=8;         indices=crossvalind('kfold',traininglabelij,numfold);         sigma=2.^(-10:1:10);         c=2.^(-5:1:5);         [bestsigma,bestc]=bestparametersrbf(trainingsampleij,...                            traininglabelij,sigma,c,indices,numfold);         %%performance         svmstruct=svmtrain(trainingsampleij,traininglabelij,...              'showplot',true,'kernel_function','rbf','rbf_sigma',bestsigma,...              'boxconstraint',bestc);         title(sprintf('kernel function: %s','rbf',...               func2str(svmstruct.kernelfunction)),...                        'interpreter','none');         classes=svmclassify(svmstruct,testingsample,'showplot',true);      end  end  acc=mean(grp2idx(classes)==grp2idx(testinglabel));

training data data used train classifier (for example svm).

test data used test performance of trained classifier.


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