covlinone.m

高斯过程在回归和分类问题中的应用

function [A, B] = covLINone(logtheta, x, z);

% Linear covariance function with a single hyperparameter. The covariance
% function is parameterized as:
%
% k(x^p,x^q) = x^p'*inv(P)*x^q + 1./t2;
%
% where the P matrix is t2 times the unit matrix. The second term plays the
% role of the bias. The hyperparameter is:
%
% logtheta = [ log(sqrt(t2)) ]
%
% For more help on design of covariance functions, try "help covFunctions".
%
% (C) Copyright 2006 by Carl Edward Rasmussen (2006-03-27)

if nargin == 0, A = '1'; return; end              % report number of parameters

it2 = exp(-2*logtheta);                                            % t2 inverse

if nargin == 2                                             % compute covariance
  A = it2*(1+x*x');
elseif nargout == 2                              % compute test set covariances
  A = it2*(1+sum(z.*z,2));
  B = it2*(1+x*z');
else                                                % compute derivative matrix
  A = -2*it2*(1+x*x');
end