Add to ORKGWe consider the problem of assigning an input vector x to one of m classes by predicting P (cjx) for c = 1; : : :;m. For a two-class problem, the probability of class 1 given x is estimated by (y(x)), where (y) = 1=(1 + e y). A Gaussian process prior is placed on y(x), and is combined with the training data to obtain predictions for new x points. We provide a Bayesian treatment, integrating over uncertainty in y and in the parameters that control the Gaussian process prior; the necessary integration over y is carried out using Laplace's approximation. The method is generalized to multi-class problems (m> 2) using the softmax function. We demonstrate the eectiveness of the method on a number of datasets. Bayesian Classication with G...