oc_set.m

模式识别工具箱,希望对大家有用!

function a = oc_set(a,clnr)
% OC_SET  makes an one-class dataset
%
% A = oc_set(A,clnr)
%
% Change a normal dataset A into an one-class dataset: the class
% indicated by the classnr (clnr) is made target class and all other
% data becomes outliers class. The labels are changed to 'target' and
% 'outlier'.
%
% It is also possible to use a class label:
%
% A = oc_set(A,label)
%
% but then the type of the label should be a char (else you cannot
% distinguish it from a class number, can you?:-))

% Copyright: D. Tax, R.P.W. Duin, [e-mail]
% Faculty of Applied Physics, Delft University of Technology
% P.O. Box 5046, 2600 GA Delft, The Netherlands

if (nargin<2)
  clnr = 1;
end

% match the labellist type with the clnr
[nlab,lablist,m,k,c] = dataset(a);
if isa(clnr,'char')
  if isa(lablist,'double')
    [nlab,clnr] = renumlab(getlab(a),str2num(clnr));
  else % lablist is character
    [nlab,clnr] = renumlab(getlab(a),clnr);
  end
end

% make the new labels:
lablist =  str2mat('target', 'outlier');
laba = ones(m,size(lablist,2));
I = find(nlab==clnr);
laba(I,:) = ones(length(I),1)*lablist(1,:);
I = find(nlab~=clnr);
laba(I,:) = ones(length(I),1)*lablist(2,:);

a = dataset(+a,char(laba));

return