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author Daniel Wolff
date Fri, 19 Aug 2016 13:07:06 +0200
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Daniel@0 1 <html>
Daniel@0 2 <head>
Daniel@0 3 <title>
Daniel@0 4 Netlab Reference Manual gtminit
Daniel@0 5 </title>
Daniel@0 6 </head>
Daniel@0 7 <body>
Daniel@0 8 <H1> gtminit
Daniel@0 9 </H1>
Daniel@0 10 <h2>
Daniel@0 11 Purpose
Daniel@0 12 </h2>
Daniel@0 13 Initialise the weights and latent sample in a GTM.
Daniel@0 14
Daniel@0 15 <p><h2>
Daniel@0 16 Synopsis
Daniel@0 17 </h2>
Daniel@0 18 <PRE>
Daniel@0 19 net = gtminit(net, options, data, samptype)
Daniel@0 20 net = gtminit(net, options, data, samptype, lsampsize, rbfsampsize)
Daniel@0 21 </PRE>
Daniel@0 22
Daniel@0 23
Daniel@0 24 <p><h2>
Daniel@0 25 Description
Daniel@0 26 </h2>
Daniel@0 27 <CODE>net = gtminit(net, options, data, samptype)</CODE> takes a GTM <CODE>net</CODE>
Daniel@0 28 and generates a sample of latent data points and sets the centres (and
Daniel@0 29 widths if appropriate) of
Daniel@0 30 <CODE>net.rbfnet</CODE>.
Daniel@0 31
Daniel@0 32 <p>If the <CODE>samptype</CODE> is <CODE>'regular'</CODE>, then regular grids of latent
Daniel@0 33 data points and RBF centres are created. The dimension of the latent data
Daniel@0 34 space must be
Daniel@0 35 1 or 2. For one-dimensional latent space, the <CODE>lsampsize</CODE> parameter
Daniel@0 36 gives the number of latent points and the <CODE>rbfsampsize</CODE> parameter
Daniel@0 37 gives the number of RBF centres. For a two-dimensional latent space,
Daniel@0 38 these parameters must be vectors of length 2 with the number of points
Daniel@0 39 in each of the x and y directions to create a rectangular grid. The
Daniel@0 40 widths of the RBF basis functions are set by a call to <CODE>rbfsetfw</CODE>
Daniel@0 41 passing <CODE>options(7)</CODE> as the scaling parameter.
Daniel@0 42
Daniel@0 43 <p>If the <CODE>samptype</CODE> is <CODE>'uniform'</CODE> or <CODE>'gaussian'</CODE> then the
Daniel@0 44 latent data is found by sampling from a uniform or
Daniel@0 45 Gaussian distribution correspondingly. The RBF basis function parameters
Daniel@0 46 are set
Daniel@0 47 by a call to <CODE>rbfsetbf</CODE> with the <CODE>data</CODE> parameter
Daniel@0 48 as dataset and the <CODE>options</CODE> vector.
Daniel@0 49
Daniel@0 50 <p>Finally, the output layer weights of the RBF are initialised by
Daniel@0 51 mapping the mean of the latent variable to the mean of the target variable,
Daniel@0 52 and the L-dimensional latent variale variance to the variance of the
Daniel@0 53 targets along the first L principal components.
Daniel@0 54
Daniel@0 55 <p><h2>
Daniel@0 56 See Also
Daniel@0 57 </h2>
Daniel@0 58 <CODE><a href="gtm.htm">gtm</a></CODE>, <CODE><a href="gtmem.htm">gtmem</a></CODE>, <CODE><a href="pca.htm">pca</a></CODE>, <CODE><a href="rbfsetbf.htm">rbfsetbf</a></CODE>, <CODE><a href="rbfsetfw.htm">rbfsetfw</a></CODE><hr>
Daniel@0 59 <b>Pages:</b>
Daniel@0 60 <a href="index.htm">Index</a>
Daniel@0 61 <hr>
Daniel@0 62 <p>Copyright (c) Ian T Nabney (1996-9)
Daniel@0 63
Daniel@0 64
Daniel@0 65 </body>
Daniel@0 66 </html>