%GENDATH Generation of Highleyman classes% %   A = GENDATH(N,LABTYPE)%% INPUT%  N        Number of objects (optional; default: [50,50])%  LABTYPE  Label type (optional; default: 'crisp')%% OUTPUT%  A        Generated dataset%% DESCRIPTION% Generation of a 2-dimensional 2-class dataset A of N objects% according to Highleyman. %% The two Highleyman classes are defined by % 1: Gauss([1 1],[1 0; 0 0.25]).% 2: Gauss([2 0],[0.01 0; 0 4]).% Class priors are P(1) = P(2) = 0.5 %% If N is a vector of sizes, exactly N(I) objects are generated% for class I, I = 1,2.%% LABTYPE defines the desired label type: 'crisp' or 'soft'. In the % latter case true posterior probabilities are set for the labels.%% Defaults: N = [50,50], LABTYPE = 'crisp'.% % EXAMPLES% PREX_PLOTC, PREX_CLEVAL%% SEE ALSO% DATASETS, GAUSS, PRDATASETS% 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: gendath.m,v 1.4 2004/01/06 07:38:01 bob Exp $function A = gendath(N,labtype)	prtrace(mfilename);		if nargin < 1, N = [50, 50]; end	if nargin < 2, labtype = 'crisp'; end	GA = [1 0; 0 0.25];	GB = [0.01 0; 0 4];	G = cat(3,GA,GB);	p = [0.5 0.5];	N = genclass(N,p);	U = dataset([1 1; 2 0],[1 2]','prior',p);	U = setprior(U,p);	A = gauss(N,U,G);	A = setname(A,'Highleyman Dataset');	switch labtype	 case 'crisp'	  ;	 case 'soft'	  W = nbayesc(U,cat(3,GA,GB));	  targets = A*W*classc;	  A = setlabtype(A,'soft',targets);	 otherwise	  error(['Label type ' labtype ' not supported'])	end	return