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<html><head><title>Netlab Reference Manual gbayes</title></head><body><H1> gbayes</H1><h2>Purpose</h2>Evaluate gradient of Bayesian error function for network.<p><h2>Synopsis</h2><PRE>g = gbayes(net, gdata)[g, gdata, gprior] = gbayes(net, gdata)</PRE><p><h2>Description</h2><CODE>g = gbayes(net, gdata)</CODE> takes a network data structure <CODE>net</CODE> together the data contribution to the error gradientfor a set of inputs and targets.It returns the regularised error gradient using any zero mean Gaussian priorson the weights defined in<CODE>net</CODE>. In addition, if a <CODE>mask</CODE> is defined in <CODE>net</CODE>, thenthe entries in <CODE>g</CODE> that correspond to weights with a 0 in themask are removed.<p><CODE>[g, gdata, gprior] = gbayes(net, gdata)</CODE> additionally returns thedata and prior components of the error.<p><h2>See Also</h2><CODE><a href="errbayes.htm">errbayes</a></CODE>, <CODE><a href="glmgrad.htm">glmgrad</a></CODE>, <CODE><a href="mlpgrad.htm">mlpgrad</a></CODE>, <CODE><a href="rbfgrad.htm">rbfgrad</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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