function c = dd_costc(a,w);%DD_COSTC Cost curve%%        C = DD_COSTC(A,W)%        C = DD_COSTC(A*W)%        C = A*W*DD_COSTC%% Find the cost curve as it is define in:%@inproceedings{ drummond00explicitly,%    author = "Chris Drummond and Robert C. Holte",%    title = "Explicitly representing expected cost: an alternative to {ROC} representation",%    booktitle = "Knowledge Discovery and Data Mining",%    pages = "198-207",%    year = "2000"},% The costs and the probability cost function are returned in a% structure containing the fields pcf and cost.%% See also: dd_roc, plotcosts, simpleroc% Copyright: D.M.J. Tax, D.M.J.Tax@prtools.org% Faculty EWI, Delft University of Technology% P.O. Box 5031, 2600 GA Delft, The Netherlandsglobal rtype;if isempty(rtype)	rtype = 'hull';endif nargin==0	c = mapping(mfilename,'fixed');elseif nargin == 1	% simplify the code by using dd_roc (where the FN and FP are already	% nicely computed):	if ~isfield(a,'err')		r = dd_roc(a);	else		r = a;	end	% find the convex hull:	switch rtype	case 'hull'		e = roc_hull(r);	case 'mid'		s = rocmid(rocsqueeze(r));		e = s.err;	case 'org'		e = r.err;	end	% first get the errors:   [FN FP]	e = e(end:-1:1,:);	% convert it into:  [FP TP]	fp = e(:,2);	fn = e(:,1);	% find the places where the curves cross:	dfp = diff(fp);	dfn = diff(fn);	pcf = dfp./(dfp-dfn);	% the last pcf is always 1 (a bit strange maybe, but with this I can	% easily perform vector operations together with fn and fp)	pcf = [pcf; 1];	% the output cost values:	cost = fp + (fn-fp).*pcf;	% store everything into one structure:	c.op = r.op;	% the first value in the curve is not a crossing of two lines and is	% added explicitly:	c.pcf = [0; pcf];	c.cost = [0; cost];else	% Separate mapping and dataset are given, so we have to map the data	% first:	ismapping(w);	istrained(w);	c = feval(mfilename,a*w);endreturn