dd_example.m

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% DD_EXAMPLE
%
% Example of the creation of a One-Class problem, and the solutions
% obtained by the Nearest Neighbor Data Description and the Support
% Vector Data Description.

% 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

% generate normal classification problem: train data:
fracrej = 0.1;
a = gendatb(50);
% make the second class the target class and change the labels:
a = oc_set(a,'B');
% only use target class:
a = target_class(a);
% generate test data:
b = oc_set(gendatb(100),'B');

% first show a 2D plot:
lw = 3;    %linewidth
ms = 10;   %markersize
fs = 16;   %fontsize
figure(1); clf; hold on; H = [0;0];
h=scatterd(a);
V = axis; axis(1.5*V);
set(h,'markersize',ms,'linewidth',lw);

% train the individual data descriptions and plot them
w1 = nndd(a,fracrej);
h = plotd(w1,'g-');
set(h,'linewidth',lw);
H(1) = h(1);
w2 = svdd(a,fracrej);
h = plotd(w2,'r--');
set(h,'linewidth',lw);
H(2) = h(1);
%legend(H,'NN dd','SVDD');
axis equal;
axis image;
fontsize(fs);

% second show the ROC curves:
figure(2); clf;hold on; H=[0;0];
% train the Nearest Neighbor method:
w = nndd;
e = dd_roc(w,a,b,0.01:0.01:0.5);
e1 = e;
h = plot2(e','g-');
H(1) = h(1);
err_nn = dd_auc(e)
% train SVDD:
w = svdd;
e = dd_roc(w,a,b);
h = plot2(e','r--');
H(2) = h(1);
err_svdd = dd_auc(e)

xlabel('Target objects rejected');
ylabel('Outlier objects accepted');
title('ROC curves');
fontsize(fs);
%legend(H,'NN dd','SVDD');