%MEANC Mean combining classifier
%
% W = MEANC(V)
% W = V*MEANC
%
% INPUT
% V Set of classifiers (optional)
%
% OUTPUT
% W Mean combiner
%
% DESCRIPTION
% If V = [V1,V2,V3, ... ] is a set of classifiers trained on the same
% classes and W is the mean combiner: it selects the class with the mean of
% the outputs of the input classifiers. This might also be used as
% A*[V1,V2,V3]*MEANC 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 V = V*CLASSC;
%
% For affine mappings the coefficients may be averaged instead of the
% classifier results by using AVERAGEC.
%
% The base classifiers may be combined in a stacked way (operating in the
% same feature space by V = [V1,V2,V3, ... ] or in a parallel way
% (operating in different feature spaces) by V = [V1;V2;V3; ... ]
%
% EXAMPLES
% PREX_COMBINING
%
% SEE ALSO (<a href="http://37steps.com/prtools">PRTools Guide</a>)
% MAPPINGS, DATASETS, VOTEC, MAXC, MINC, MEDIANC, PRODC,
% AVERAGEC, STACKED, PARALLEL
% Copyright: R.P.W. Duin, r.p.w.duin@37steps.com
% Faculty EWI, Delft University of Technology
% P.O. Box 5031, 2600 GA Delft, The Netherlands
% $Id: meanc.m,v 1.3 2010/06/01 08:48:55 duin Exp $
function w = meanc(p1)
type = 'mean'; % define the operation processed by FIXEDCC.
name = 'Mean combiner'; % define the name of the combiner.
% this is the general procedure for all possible
% calls of fixed combiners handled by FIXEDCC
if nargin == 0
w = prmapping('fixedcc','combiner',{[],type,name});
else
w = fixedcc(p1,[],type,name);
end
if isa(w,'prmapping')
w = setname(w,name);
end
return