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/demhmc2.htm | 45 +++++++++++++++++++++++++++ 1 file changed, 45 insertions(+) create mode 100644 sourcecodes/bnt-master/nethelp3.3/demhmc2.htm (limited to 'sourcecodes/bnt-master/nethelp3.3/demhmc2.htm') diff --git a/sourcecodes/bnt-master/nethelp3.3/demhmc2.htm b/sourcecodes/bnt-master/nethelp3.3/demhmc2.htm new file mode 100644 index 00000000..b5657cbe --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/demhmc2.htm @@ -0,0 +1,45 @@ + + + +Netlab Reference Manual demhmc2 + + + +

demhmc2 +

+Purpose +

+Demonstrate Bayesian regression with Hybrid Monte Carlo sampling. + +

+Synopsis +

+demhmc2

+ + +

+Description +

+The problem consists of one input variable x and one target variable +t with data generated by sampling x at equal intervals and then +generating target data by computing sin(2*pi*x) and adding Gaussian +noise. The model is a 2-layer network with linear outputs, and the hybrid Monte +Carlo algorithm (without persistence) is used to sample from the posterior +distribution of the weights. The graph shows the underlying function, +100 samples from the function given by the posterior distribution of the +weights, and the average prediction (weighted by the posterior probabilities). + +

+See Also +

+demhmc3, hmc, mlp, mlperr, mlpgrad

+Pages: +Index +