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/mlpgrad.htm | 51 +++++++++++++++++++++++++++ 1 file changed, 51 insertions(+) create mode 100644 sourcecodes/bnt-master/nethelp3.3/mlpgrad.htm (limited to 'sourcecodes/bnt-master/nethelp3.3/mlpgrad.htm') diff --git a/sourcecodes/bnt-master/nethelp3.3/mlpgrad.htm b/sourcecodes/bnt-master/nethelp3.3/mlpgrad.htm new file mode 100644 index 00000000..08943cc9 --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/mlpgrad.htm @@ -0,0 +1,51 @@ + + + +Netlab Reference Manual mlpgrad + + + +

mlpgrad +

+Purpose +

+Evaluate gradient of error function for 2-layer network. + +

+Synopsis +

+
+g = mlpgrad(net, x, t)
+

+ + +

+Description +

+g = mlpgrad(net, x, t) takes a network data structure net +together with a matrix x of input vectors and a matrix t +of target vectors, and evaluates the gradient g of the error +function with respect to the network weights. The error funcion +corresponds to the choice of output unit activation function. Each row +of x corresponds to one input vector and each row of t +corresponds to one target vector. + +

[g, gdata, gprior] = mlpgrad(net, x, t) also returns separately +the data and prior contributions to the gradient. In the case of +multiple groups in the prior, gprior is a matrix with a row +for each group and a column for each weight parameter. + +

+See Also +

+mlp, mlppak, mlpunpak, mlpfwd, mlperr, mlpbkp

+Pages: +Index +