Exact expected NN error from a dissimilarity matrix (1)
E = NNERROR1(D,M)
Exact computation of the expected 1-nearest neighbor error. D should be a dataset containing a labeled square dissimilarity matrix of a set of objects related to itself. It is not needed that D is symmetric. So NNERROR1(D) ~= NNERROR1(D') is possible.
E = NNERROR1(D)
In this case a set of training set sizes is used to produce a full learning curve. E can be plotted by PLOTE.
There is a similar routine NNERROR2 which is based on the selection of an equal number of objects per class.