gendatout.m

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function z = gendatout(a,n,dR)
% z = gendatout(a,n)
%
% Generate outlier objects in a hypersphere round dataset a. This
% dataset should be a one-class dataset. The hypersphere is calculated
% from SVDD.
%
% z = gendatout(a,n,dR)
%
% The radius can be enlarge by a certain fraction:  r' = dR*r_org.

% 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<3)
  dR = 1;
end

% what is our target data?
a = +target_class(a);

% compute SVDD with very big s:
s_max = max(max(distm(a)));
[nra,dim] = size(a);
[svx,alf,b]=m_svm(+a,ones(nra,1),2,2,s_max,1/nra,1e-4);

% compute from SVDD the mean and radius
nrsv = size(svx,1);
meana = sum(svx.*(alf*ones(1,dim)));
R = sqrt(mean(sum((svx-(ones(nrsv,1)*meana)).^2,2)));
R = dR*R;

% generate new data
z = ones(n,1)*meana + randsph(n,dim)*R;
%label it as outliers
%z = oc_set(dataset([a;z],[ones(size(a,1),1); 2*ones(n,1)]),1);
labz = genlab([size(a,1),n],['target ';'outlier']);
z = dataset([a;z],labz);

return