k-nearest neighbor classifier based on a distance matrix D. k==1 is much faster than k>1. For k>1, ties are broken randomly. USAGE IDXpred = clfKnnDist( D, IDX, k ) INPUTS D - MxN array of distances from M-TEST points to N-TRAIN points. IDX - nTrain length vector of class memberships k - [1] number of nearest neighbors to use OUTPUTS IDXpred - length M vector of classes for training data EXAMPLE % (given D and IDX) for k=1:size(D,2) err(k)=sum(IDX==clfKnnDist(D,IDX,k)); end; figure(1); plot(err) See also CLFKNN