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📄 prodc.m

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%PRODC Product combining classifier% % 	W = prodc(V)% 	W = V*prodc% % If V = [V1,V2,V3, ... ] is a set of classifiers trained on the % same classes and W is the product combiner: it selects the class % with the product of the outputs of the input classifiers. This % might also be used as A*[V1,V2,V3]*prodc in which A is a dataset % to be classified.% % If it is desired to operate on posterior probabilities then the % input classifiers should be extended like V1 = classc(V1).% % See also mappings, datasets, meanc, maxc, minc, majorc, medianc% Copyright: R.P.W. Duin, duin@ph.tn.tudelft.nl% Faculty of Applied Physics, Delft University of Technology% P.O. Box 5046, 2600 GA Delft, The Netherlandsfunction v = prodc(a)if nargin == 0	v = mapping('prodc','combiner');elseif nargin == 1 & isa(a,'mapping')	[nclass,classlist] = renumlab(getfeat(a));	v = a*mapping('prodc',NaN,classlist,size(a,2),size(classlist,1));else	[nlab,lablist,m,ka,ca,prob,featlist,imheight] = dataset(a); 	[nclass,classlist] = renumlab(featlist);	c = size(classlist,1);	v = dataset(zeros(m,c),getlab(a),classlist,prob,lablist,imheight);	for j=1:c		J = find(nclass==j);		v(:,j) = exp(mean(log(a(:,J)+1e-100),2));	endend

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