From 8070dc963753142bb86c4ed698d91fd623ed28e7 Mon Sep 17 00:00:00 2001 From: ziejd2 Date: Thu, 28 Sep 2017 15:04:40 -0500 Subject: BNW using Octave instead of Matlab. This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning. I am calling this BNW_1.02. It can be accessed at: compbio.uthsc.edu/BNW_1.02 --- sourcecodes/bnt-master/nethelp3.3/netevfwd.htm | 52 ++++++++++++++++++++++++++ 1 file changed, 52 insertions(+) create mode 100644 sourcecodes/bnt-master/nethelp3.3/netevfwd.htm (limited to 'sourcecodes/bnt-master/nethelp3.3/netevfwd.htm') diff --git a/sourcecodes/bnt-master/nethelp3.3/netevfwd.htm b/sourcecodes/bnt-master/nethelp3.3/netevfwd.htm new file mode 100644 index 00000000..ea876bb2 --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/netevfwd.htm @@ -0,0 +1,52 @@ + + + +Netlab Reference Manual netevfwd + + + +

netevfwd +

+Purpose +

+Generic forward propagation with evidence for network + +

+Synopsis +

+
+[y, extra] = netevfwd(w, net, x, t, x_test)
+[y, extra, invhess] = netevfwd(w, net, x, t, x_test, invhess)
+

+ + +

+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

+Pages: +Index +