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Diffstat (limited to 'sourcecodes/bnt-master/netlab3.3/netevfwd.m')
| -rw-r--r-- | sourcecodes/bnt-master/netlab3.3/netevfwd.m | 29 |
1 files changed, 29 insertions, 0 deletions
diff --git a/sourcecodes/bnt-master/netlab3.3/netevfwd.m b/sourcecodes/bnt-master/netlab3.3/netevfwd.m new file mode 100644 index 00000000..26bb25aa --- /dev/null +++ b/sourcecodes/bnt-master/netlab3.3/netevfwd.m @@ -0,0 +1,29 @@ +function [y, extra, invhess] = netevfwd(w, net, x, t, x_test, invhess) +%NETEVFWD Generic forward propagation with evidence for network +% +% Description +% [Y, EXTRA] = NETEVFWD(W, NET, X, T, X_TEST) takes a network data +% structure NET together with the input X and target T training data +% and input test data X_TEST. It returns the normal forward propagation +% through the network Y together with a matrix EXTRA which consists of +% error bars (variance) for a regression problem or moderated outputs +% for a classification problem. +% +% The optional argument (and return value) INVHESS is the inverse of +% the network Hessian computed on the training data inputs and targets. +% Passing it in avoids recomputing it, which can be a significant +% saving for large training sets. +% +% See also +% MLPEVFWD, RBFEVFWD, GLMEVFWD, FEVBAYES +% + +% Copyright (c) Ian T Nabney (1996-2001) + +func = [net.type, 'evfwd']; +net = netunpak(net, w); +if nargin == 5 + [y, extra, invhess] = feval(func, net, x, t, x_test); +else + [y, extra, invhess] = feval(func, net, x, t, x_test, invhess); +end |