%TRAINCC Train combining classifier if needed% %   W = TRAINCC(A,W,CCLASSF)% % INPUT%   A        Training dataset%   W        A set of classifiers to be combined  %   CCLASSF  Combining classifier%% OUTPUT%   B        Combined classifier mapping%% DESCRIPTION  % The combining classifier CCLASSF is trained by the dataset A*W, if% training is needed. W is typically a set of stacked (operating in the same% feature space) or parallel (operating in different feature spaces;% performed one after another) classifiers to be combined. E.g. if V1, V2% and V3 are base classifiers, then V = [V1,V2,V3,...] is a stacked% classifier and V = [V1;V2;V3;...] is a parallel one. If CCLASSF is one of% the fixed combining rules like MAXC, then training is skipped.%% This routine is typically called by combining classifier schemes like% BAGGINGC and BOOSTINGC.%% SEE ALSO% DATASETS, MAPPINGS, STACKED, PARALLEL, BAGGINGC, BOOSTINGC% 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: traincc.m,v 1.4 2003/09/15 07:09:52 bob Exp $function w = traincc(a,w,cclassf)	prtrace(mfilename);	if (~ismapping(cclassf))		error('Combining classifier is an unknown mapping.')	end	% If CCLASSF is already a combining classifier, just apply it. Otherwise,	% train it using A*W.	if (iscombiner(cclassf))		w = w*cclassf;	else		w = w*(a*w*cclassf);	end	w = setcost(w,a);	return