make_outliers.m

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function [b,blck] = make_outliers(a,n,scale)
% MAKE_OUTLIERS
%
%   [b,blck] = make_outliers(a,n,scale)
%
% Add an uniform outlier distribution to the given OC dataset a and
% create a new dataset b. Dataset should contain a target class (with
% the label 'target '.  All other data will be deleted. The
% n new outliers will be drawn from a block defined around dataset a.
% The size of the box can be adjusted by scale (default 2, which means
% the edge of the box is twice the maximum distance in the respective
% feature direction).
%
% When n=0 is given, no outliers are created, but the dataset with
% only the first class is created and the box is computed.
%
%   [b,blck] = make_outliers(a,n,blck)
% 
% The user now defines the block where the data should be created. The
% format of the block is   blck=[minx max; miny maxy ] 
%
%   [b,blck] = make_outliers(a)
% Now the same number of target objects and outlier objects are
% created.
%
% In the case of 2D data is also possible to use a grid of objects. In
% that case n should be <0.
%
% Dxd, 20-04-2000

% 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)
  scale = 2.0;
end
if (nargin<2)  % if no required number is given, copy from a:
  n = size(a,1);
end

% well, find the target class:
a = target_class(a);
lablist = str2mat('target','outlier');
[m,k] = size(a);

% create the outlier box:
if (max(size(scale))>1)         % the block is known
  blck = scale;
else
  blck = [min(a)' max(a)'];     % the block has to be defined
  df = diff(blck,1,2);
  meanval = mean(blck,2);
  newscale = scale/2;
  blck = [meanval-newscale*df, meanval+newscale*df];
end

% combine it to a dataset:
if (n>0)  % we randomly draw uniform data:
  b = [+a; (ones(n,1)*blck(:,1)') + ...
          (ones(n,1)*diff(blck,1,2)').*rand(n,k)];
else
  if k==2
    grid = gendatgrid([],[30 30],blck(:,1),blck(:,2));
    b = [+a; grid];
    n = size(grid,1);
  else
    warning('Data should be 2D');
  end
end
labb = [ones(m,1)*lablist(1,:); ones(n,1)*lablist(2,:)];

b = dataset(b,char(labb),getfeat(a),[],lablist);

return