%NMC Nearest Mean Classifier% %   W = NMC(A)%% INPUT%   A    Dataset%% OUTPUT%   W    Nearest Mean Classifier   %% DESCRIPTION% Computation of the nearest mean classifier between the classes in the% dataset A.  The use of soft labels is supported.%% SEE ALSO% DATASETS, MAPPINGS, NMSC, LDC, FISHERC, QDC, UDC % Copyright: R.P.W. Duin, duin@ph.tn.tudelft.nl% Faculty of Applied Sciences, Delft University of Technology% P.O. Box 5046, 2600 GA Delft, The Netherlands% $Id: nmc.m,v 1.9 2004/12/06 07:38:27 duin Exp $function W = nmc(a)		prtrace(mfilename);		if nargin < 1 | isempty(a)		W = mapping(mfilename);		W = setname(W,'Nearest Mean');		return	end		islabtype(a,'crisp','soft');	isvaldset(a,1,2); % at least 1 object per class, 2 classes	[m,k,c] = getsize(a);	u = meancov(a);	if c == 2      % 2-class case: store linear classifier		u1 = +u(1,:);		u2 = +u(2,:);		R = [u1-u2]';		offset =(u2*u2' - u1*u1')/2;		W = affine([R -R],[offset -offset],a,getlablist(a));		W = cnormc(W,a);		W = setname(W,'Nearest Mean');	else           % multiclass case, store as 1-nn classifier, best thing to do?		W = knnc(u,1);		W = setname(W,'Nearest Mean');	end	W = setcost(W,a); 		return