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<html><head><title>Netlab Reference Manual gp</title></head><body><H1> gp</H1><h2>Purpose</h2>Create a Gaussian Process.<p><h2>Synopsis</h2><PRE>net = gp(nin, covarfn)net = gp(nin, covarfn, prior)</PRE><p><h2>Description</h2><p><CODE>net = gp(nin, covarfn)</CODE> takes the number of inputs <CODE>nin</CODE> for a Gaussian Process model with a single output, togetherwith a string <CODE>covarfn</CODE> which specifies the type of the covariance function,and returns a data structure <CODE>net</CODE>. The parameters are set to zero.<p>The fields in <CODE>net</CODE> are<PRE> type = 'gp' nin = number of inputs nout = number of outputs: always 1 nwts = total number of weights and covariance function parameters bias = logarithm of constant offset in covariance function noise = logarithm of output noise variance inweights = logarithm of inverse length scale for each input covarfn = string describing the covariance function: 'sqexp' 'ratquad' fpar = covariance function specific parameters (1 for squared exponential, 2 for rational quadratic) trin = training input data (initially empty) trtargets = training target data (initially empty)</PRE><p><CODE>net = gp(nin, covarfn, prior)</CODE> sets a Gaussian prior on theparameters of the model. <CODE>prior</CODE> must contain the fields<CODE>pr_mean</CODE> and <CODE>pr_variance</CODE>. If <CODE>pr_mean</CODE> is a scalar,then the Gaussian is assumed to be isotropic and the additional fields<CODE>net.pr_mean</CODE> and <CODE>pr_variance</CODE> are set. Otherwise, the Gaussian prior has a meandefined by a column vector of parameters <CODE>prior.pr_mean</CODE> andcovariance defined by a column vector of parameters <CODE>prior.pr_variance</CODE>.Each element of <CODE>prmean</CODE> corresponds to a separate group of parameters, whichneed not be mutually exclusive. The membership of the groups is definedby the matrix <CODE>prior.index</CODE> in which the columns correspond to the elements of<CODE>prmean</CODE>. Each column has one element for each weight in the matrix,in the order defined by the function <CODE>gppak</CODE>, and each elementis 1 or 0 according to whether the parameter is a member of thecorresponding group or not. The additional field <CODE>net.index</CODE> is setin this case.<p><h2>See Also</h2><CODE><a href="gppak.htm">gppak</a></CODE>, <CODE><a href="gpunpak.htm">gpunpak</a></CODE>, <CODE><a href="gpfwd.htm">gpfwd</a></CODE>, <CODE><a href="gperr.htm">gperr</a></CODE>, <CODE><a href="gpcovar.htm">gpcovar</a></CODE>, <CODE><a href="gpgrad.htm">gpgrad</a></CODE><hr><b>Pages:</b><a href="index.htm">Index</a><hr><p>Copyright (c) Ian T Nabney (1996-9)</body></html>⌨️ 快捷键说明
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