d2wef_snn.m

神经网络的工具箱, 神经网络的工具箱,

function H = d2wef_snn(y, t, g, errf) 
%D2WEF_SNN 2nd derivative of wef_snn with respect to y.

[n, q] = size(y);
nf = 1/(sum(g(find(~isnan(g)))));
g = nf * g;

%#function se_snn d2se_snn
%#function relerr_snn d2relerr_snn
%#function loglikelihood_snn d2loglikelihood_snn 
%#function crosslogistic_snn d2crosslogistic_snn
%#function crossentropy_snn d2crossentropy_snn
H = sparse(n,q);
if isstr(errf)
   ii = find(~isnan(g));
   H(ii) = g(ii) .* feval(feval(errf, '2deriv'), y(ii), t(ii));
elseif (size(errf,2) == 1)
   for i = 1:size(y,1)
       mu = find(~isnan(g(i,:)));
       H(i,mu) = g(i,mu) .* ...
                     feval(feval(errf{i,1}, '2deriv'), y(i,mu), t(i,mu));
   end
else
   for i = 1:size(y,1)
       for mu = find(~isnan(g(i,:))); 
           H(i, mu) = g(i, mu) * ...
	         feval(feval(errf{i,mu}, '2deriv'), y(i,mu), t(i,mu));
       end
   end
end

H = sparse(diag(reshape(H, n*q,1)));