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/mdn2gmm.htm | 58 +++++++++++++++++++++++++++
1 file changed, 58 insertions(+)
create mode 100644 sourcecodes/bnt-master/nethelp3.3/mdn2gmm.htm
(limited to 'sourcecodes/bnt-master/nethelp3.3/mdn2gmm.htm')
diff --git a/sourcecodes/bnt-master/nethelp3.3/mdn2gmm.htm b/sourcecodes/bnt-master/nethelp3.3/mdn2gmm.htm
new file mode 100644
index 00000000..51369a50
--- /dev/null
+++ b/sourcecodes/bnt-master/nethelp3.3/mdn2gmm.htm
@@ -0,0 +1,58 @@
+
+
+
+Netlab Reference Manual mdn2gmm
+
+
+
+ mdn2gmm
+
+
+Purpose
+
+Converts an MDN mixture data structure to array of GMMs.
+
+
+Synopsis
+
+
+gmmmixes = mdn2gmm(mdnmixes)
+
+
+
+
+Description
+
+gmmmixes = mdn2gmm(mdnmixes) takes an MDN mixture data structure
+mdnmixes
+containing three matrices (for priors, centres and variances) where each
+row represents the corresponding parameter values for a different mixture model
+and creates an array of GMMs. These can then be used with the standard
+Netlab Gaussian mixture model functions.
+
+
+Example
+
+
+
+mdnmixes = mdnfwd(net, x);
+mixes = mdn2gmm(mdnmixes);
+p = gmmprob(mixes(1), y);
+
+
+This creates an array GMM mixture models (one for each data point in
+x). The vector p is then filled with the conditional
+probabilities of the values y given x(1,:).
+
+
+See Also
+
+gmm, mdn, mdnfwd
+Pages:
+Index
+
+Copyright (c) Ian T Nabney (1996-9)
+
David J Evans (1998)
+
+
+
\ No newline at end of file
--
cgit 1.4.1