_PROBLEM CoEPrA-2006_Classification_002

_GROUP_NAME Gavin Cawley

_GROUP_MEMBERS
Gavin Cawley

_ADDRESS
School of Computing Science
University of East Anglia
Norwich NR4 7TJ, U. K.

_MODELLING_PROCEDURE

The training data are first standardised.  A Gaussian Process
classifier is trained using the expectation propagation
procedure, using an isotropic squared exponential kernel.
The hyper-parameters of the model were selected by maximising
the marginal likelihood.  The model is completely specified by
the training data and the hyper-parameters:

length-scale    = 104.998622
signal variance = 3521.896006

Leave-one-out cross-validation results:

Accuracy              = 0.855263
AUROC (raw scores)    = 0.939016
AUROC (binary scores) = 0.731809

Something is likely to be wrong if the test scores are
significantly different

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