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authorziejd22017-09-28 15:04:40 -0500
committerziejd22017-09-28 15:04:40 -0500
commit8070dc963753142bb86c4ed698d91fd623ed28e7 (patch)
treed0f6dd8fc46a49b819aa55c1a90faa14d8448883 /sourcecodes/bnt-master/nethelp3.3/netpak.htm
parent7cc31810d53176e805532b2789955f4eedbce6bb (diff)
downloadBNW-8070dc963753142bb86c4ed698d91fd623ed28e7.tar.gz
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
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+<html>
+<head>
+<title>
+Netlab Reference Manual netpak
+</title>
+</head>
+<body>
+<H1> netpak
+</H1>
+<h2>
+Purpose
+</h2>
+Combines weights and biases into one weights vector.
+
+<p><h2>
+Synopsis
+</h2>
+<PRE>
+w = netpak(net)
+</PRE>
+
+
+<p><h2>
+Description
+</h2>
+<CODE>w = netpak(net)</CODE> takes a network data structure <CODE>net</CODE> and
+combines the component weight matrices  into a single row
+vector <CODE>w</CODE>. The facility to switch between these two
+representations for the network parameters is useful, for example, in
+training a network by error function minimization, since a single
+vector of parameters can be handled by general-purpose optimization
+routines.  This function also takes into account a <CODE>mask</CODE> defined
+as a field in <CODE>net</CODE> by removing any weights that correspond to
+entries of 0 in the mask.
+
+<p><h2>
+See Also
+</h2>
+<CODE><a href="net.htm">net</a></CODE>, <CODE><a href="netunpak.htm">netunpak</a></CODE>, <CODE><a href="netfwd.htm">netfwd</a></CODE>, <CODE><a href="neterr.htm">neterr</a></CODE>, <CODE><a href="netgrad.htm">netgrad</a></CODE><hr>
+<b>Pages:</b>
+<a href="index.htm">Index</a>
+<hr>
+<p>Copyright (c) Ian T Nabney (1996-9)
+
+
+</body>
+</html>
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