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/gpinit.htm | 76 ++++++++++++++++++++++++++++ 1 file changed, 76 insertions(+) create mode 100644 sourcecodes/bnt-master/nethelp3.3/gpinit.htm (limited to 'sourcecodes/bnt-master/nethelp3.3/gpinit.htm') diff --git a/sourcecodes/bnt-master/nethelp3.3/gpinit.htm b/sourcecodes/bnt-master/nethelp3.3/gpinit.htm new file mode 100644 index 00000000..1874dde7 --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/gpinit.htm @@ -0,0 +1,76 @@ + + + +Netlab Reference Manual gpinit + + + +

gpinit +

+Purpose +

+Initialise Gaussian Process model. + +

+Synopsis +

+net = gpinit(net, trin, trtargets, prior)
+net = gpinit(net, trin, trtargets, prior)
+

+ + +

+Description +

+net = gpinit(net, trin, trtargets) takes a Gaussian Process data structure net +together +with a matrix trin of training input vectors and a matrix trtargets of +training target +vectors, and stores them in net. These datasets are required if +the corresponding inverse covariance matrix is not supplied to gpfwd. +This is important if the data structure is saved and then reloaded before +calling gpfwd. +Each row +of trin corresponds to one input vector and each row of trtargets +corresponds to one target vector. + +

net = gpinit(net, trin, trtargets, prior) additionally initialises the +parameters in net from the prior data structure which contains the +mean and variance of the Gaussian distribution which is sampled from. + +

+Example +

+Suppose that a Gaussian Process model is created and trained with input data x +and targets t: +

+
+net = gp(2, 'sqexp');
+net = gpinit(net, x, t);
+% Train the network
+save 'gp.net' net;
+

+ +Another Matlab program can now read in the network and make predictions on a data set +testin: +

+
+load 'gp.net';
+pred = gpfwd(net, testin);
+

+ + +

+See Also +

+gp, gpfwd

+Pages: +Index +