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1 <html>
2 <head>
3 <title>
4 Netlab Reference Manual gpunpak
5 </title>
6 </head>
7 <body>
8 <H1> gpunpak
9 </H1>
10 <h2>
11 Purpose
12 </h2>
13 Separates hyperparameter vector into components.
14
15 <p><h2>
16 Synopsis
17 </h2>
18 <PRE>
19 net = gpunpak(net, hp)
20 </PRE>
21
22
23 <p><h2>
24 Description
25 </h2>
26 <CODE>net = gpunpak(net, hp)</CODE> takes an Gaussian Process data structure <CODE>net</CODE> and
27 a hyperparameter vector <CODE>hp</CODE>, and returns a Gaussian Process data structure
28 identical to
29 the input model, except that the covariance bias
30 <CODE>bias</CODE>, output noise <CODE>noise</CODE>, the input weight vector
31 <CODE>inweights</CODE> and the vector of covariance function specific parameters
32 <CODE>fpar</CODE> have all
33 been set to the corresponding elements of <CODE>hp</CODE>.
34
35 <p><h2>
36 See Also
37 </h2>
38 <CODE><a href="gp.htm">gp</a></CODE>, <CODE><a href="gppak.htm">gppak</a></CODE>, <CODE><a href="gpfwd.htm">gpfwd</a></CODE>, <CODE><a href="gperr.htm">gperr</a></CODE>, <CODE><a href="gpgrad.htm">gpgrad</a></CODE><hr>
39 <b>Pages:</b>
40 <a href="index.htm">Index</a>
41 <hr>
42 <p>Copyright (c) Ian T Nabney (1996-9)
43
44
45 </body>
46 </html>