function net = train(net, tutor, varargin)

% TRAIN
%
% Train a dag-svm multi-class support vector classifier network using the
% specified tutor to train each component two-class network.  
% 
%    load data/iris x y;
%
%    C      = 100;
%    kernel = rbf(0.5);
%    tutor  = smosvctutor;
%
%    net = train(dagsvm, tutor, x, y, C, kernel);

%
% File        : @dagsvm/train.m
%
% Date        : Wednesday 13th September 2000
%
% Author      : Dr Gavin C. Cawley
%
% Description : Gateway function used to train a max-win multi-class support
%               vector classifier network using a given tutor.  Part of an
%               object-oriented implementation of Vapnik's Support Vector
%               Machine, as described in [1].
%

x = varargin{1};
y = varargin{2};
n = 1;

for i=1:size(y, 2)

   for j=1:i-1

      idx = [find(y(:,i) > 0) ; find(y(:,j) > 0)];

      varargin{1} = x(idx,:); 

      varargin{2} = y(idx,i); 

      net.net(n) = train(svc, tutor, varargin{:});

      n = n + 1;

   end

end

% bye bye...