valid_errorate.m

cluster validation tools matlab toolbox

function Rerror = valid_errorate(labels, truelabels)
% computing error rates for every clusters if true labels are given

nrow = length(truelabels);
[R, truelabels] = ind2cluster(truelabels);
[truelabels, S] = sort(truelabels);
labels = labels(S);
R = ind2cluster(labels);
k = length(R);

S = ones(nrow,1);
high=[];
for i = 1:k
   high(i)=mean(R{i});
end
[low, high]=sort(high);

for i = 1:k
   low=high(i);
   low=R{low};
   S(low)=i;
   vtype=S(low)-truelabels(low);
   vtype=nonzeros(vtype);
   vtype=length(vtype);
   Rerror=100*vtype/length(low);
   fprintf('\n Error rate of cluster %d : %4.2f %%',i, Rerror);
end

S=S-truelabels;
S=nonzeros(S);
S=length(S);
Rerror=100*S/nrow;
fprintf('\n Error rate for all the data: %4.2f %% \n',Rerror);