evaluate.m

支持向量机（SVM）的一些相关MATLAB程序

function K = evaluate(ker, x1, x2)

% EVALUATE
%
% Evaluate a Gaussian radial basis kernel, for example
%
%    K = evaluate(kernel, x1, x2);
%
% where x1 and x2 are matrices containing input patterns, where each column
% represents a variable and each row represents an observation.

%
% File        : @rbf/evaluate.m
%
% Date        : Tuesday 12th September 2000 
%
% Author      : Dr Gavin C. Cawley
%
% Description : Evaluate a Gaussian radial basis kernel.  Part of an
%               object-oriented implementation of Vapnik's Support
%               Vector Machine, as described in [1].  
%
% References  : [1] V.N. Vapnik,
%                   "The Nature of Statistical Learning Theory",
%                   Springer-Verlag, New York, ISBN 0-387-94559-8,
%                   1995.
%
% Note        : A faster, memory efficient mex implementation is also suplied.
%
% History     : 07/07/2000 - v1.00
%               12/09/2000 - v1.01 minor improvements to comments and help
%                                  messages.
%
% Copyright   : (c) Dr Gavin C. Cawley, September 2000.
%
%    This program is free software; you can redistribute it and/or modify
%    it under the terms of the GNU General Public License as published by
%    the Free Software Foundation; either version 2 of the License, or
%    (at your option) any later version.
%
%    This program is distributed in the hope that it will be useful,
%    but WITHOUT ANY WARRANTY; without even the implied warranty of
%    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
%    GNU General Public License for more details.
%
%    You should have received a copy of the GNU General Public License
%    along with this program; if not, write to the Free Software
%    Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
%

n = size(x2,1);
m = size(x1,1);
K = zeros(m,n);

if (m <= n)
   for p = 1:m
      K(p,:) = sum((ones(n,1)*x1(p,:) - x2).^2,2).';
   end
else
   for p = 1:n
      K(:,p) = sum((x1 - ones(m,1)*x2(p,:)).^2,2);
   end
end

K = exp(-ker.gamma*K);

% bye bye...