Missing a claas during classification of SVM

e= load('data')

k=5; f=12;

n=e.n(:,1:12);

data=n(randsample(1:length(n),length(n)),:);

truth=n(:,features+1);

c = cvpartition(truth,'KFold',k)

for i= 1:k

trIdx = c.training(i);

teIdx = c.test(i);

Model = fitcecoc(data(trIdx,:),truth(trIdx,:))

[class,s]= predict (Model,data(teIdx,:));

end

the bold line afte rthe for loop completes the Model misses on of the class during any iteration i.e

during 1st iteration model have 4 class names (as my data originaly ha)

but in 2nd iteration or may be other iteration the classifier misses or ignores one class i.e gives [1 3 4] instead of [1 2 3 4]