wolffd@0: wolffd@0: wolffd@0: wolffd@0: Netlab Reference Manual gperr wolffd@0: wolffd@0: wolffd@0: wolffd@0:

gperr wolffd@0:

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wolffd@0: Purpose wolffd@0:

wolffd@0: Evaluate error function for Gaussian Process. wolffd@0: wolffd@0:

wolffd@0: Synopsis wolffd@0:

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wolffd@0: edata = gperr(net, x, t)
wolffd@0: [e, edata, eprior] = gperr(net, x, t)
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wolffd@0: Description wolffd@0:

wolffd@0: e = gperr(net, x, t) takes a Gaussian Process data structure net together wolffd@0: with a matrix x of input vectors and a matrix t of target wolffd@0: vectors, and evaluates the error function e. Each row wolffd@0: of x corresponds to one input vector and each row of t wolffd@0: corresponds to one target vector. wolffd@0: wolffd@0:

[e, edata, eprior] = gperr(net, x, t) additionally returns the wolffd@0: data and hyperprior components of the error, assuming a Gaussian wolffd@0: prior on the weights with mean and variance parameters prmean and wolffd@0: prvariance taken from the network data structure net. wolffd@0: wolffd@0:

wolffd@0: See Also wolffd@0:

wolffd@0: gp, gpcovar, gpfwd, gpgrad
wolffd@0: Pages: wolffd@0: Index wolffd@0:
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Copyright (c) Ian T Nabney (1996-9) wolffd@0: wolffd@0: wolffd@0: wolffd@0: