wcf_snn.m

来自「神经网络的工具箱, 神经网络的工具箱,」· M 代码 · 共 101 行

function [E, Eimu] = wcf_snn(X, net, data)
%WCF_SNN Weighted cost function.
%
%Syntax
%
%  1. [cost, Eimu] = wcf_snn(net, wcfdata)
%  2. [cost, Eimu] = wcf_snn(X, net, wcfdata)
%  3. costfcn_struct = wcf_snn('pdefaults')
%
%Description
%
%  WCF_SNN computes the following cost function:
%
%  cost(y, t) =  sum_{ \{i, \mu | \Delta_{i\mu} = 1\} } 
%                   a_i g_{\mu} e^i(y_{i\mu}, t_{i\mu})
%
%   with:
%    i            - output index
%    \mu          - pattern index
%    a_i          - output weight
%    g_{\mu}      - pattern weight
%    e^i          - error function for output i
%    y_{i\mu}     - prediction for output i, pattern \mu.
%    t_{i\mu}     - target for output i, pattern \mu.
%   \Delta_{i\mu} - parameter controlling over which outputs for
%                   which patterns the summation is done
%
%  1. WCF_SNN(net, wcfdata) takes
%   net     - a net_struct with error function WCF_SNN.
%   wcfdata - a wcfdata_struct containing input/output patterns.   
%  and returns
%   cost    - the total weighted cost.  
%   Eimu    - the weighted error for each (output, pattern) pair.
%
%  2. WCF_SNN(X, net, wcfdata) takes
%   X       - additional vector with connection weights and biases,
%             which are used to compute the cost instead of the
%             connenction weights and biases in 'net'.
%
%  3. The field 'costFcn' of 'net' must contain a stucture with the cost
%   function parameters. The default parameters can be set with
%
%   net = set_net_costfcn_snn(net, wcf_snn('pdefaults'));
%
%  (NL = #outputs)
%
%Example
%
%   MU = 5;
%   P = rand(2, MU);
%   T = rand(1, MU); 
%   gmu = [1 2 2 1 1];
%   Delta = [1 0 1 0 1];
%   wcfdata = wcfdata_struct_snn(P, T, gmu, Delta)
%   net = net_struct_snn([2 4 1], {'tansigtf_snn', 'lintf_snn'},'trainlm_snn');
%   wcf_snn(net, wcfdata)
%
% See Also
%
%   NET_STRUCT_SNN, WCF_STRUCT_SNN, WCFDATA_STRUCT_SNN
%

if (isstr(X))
   switch lower(X)
     case 'deriv',
          E = 'dwcf_snn';
     case '2deriv',
          E = 'd2wcf_snn';
     case 'argmin',
          E = 'argmin_wcf_snn';
     case 'pdefaults',
	  E = wcf_struct_snn;
     otherwise,
          error('Unrecognized code.')
   end 
   return
end

if (nargin == 2)             % wcf_snn(net, data)
   data = net;
   net = X;
elseif (nargin == 3)         % wcf_snn(X, net, data)
   net = setx_snn(net, X);
else
   error('Incorrect number of input arguments');
end

% special: if isfield(data.Y) then ignore network outputs and compute
% cost from E(data.Y, data.T);
if isfield(data, 'Y')
   y = data.Y;
else
   y = simff_snn(net, data);
end

g = getg_snn(net, data);
errf = net.costFcn.fn;

[E, Eimu] = wef_snn(y, data.T, g, errf);