# gperr

## Purpose

Evaluate error function for Gaussian Process.

## Synopsis

    edata = gperr(net, x, t)
    [e, edata, eprior] = gperr(net, x, t)

## Description

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

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

## See Also

`gp`, `gpcovar`, `gpfwd`, `gpgrad`

Pages: Index

Copyright (c) Ian T Nabney (1996-9)