demmlp1
x1 is sampled uniformly from the range (0,1) and has
a low level of added Gaussian noise, x2 is a copy of x1
with a higher level of added noise, and x3 is sampled randomly
from a Gaussian distribution. The single target variable is determined
by sin(2*pi*x1) with additive Gaussian noise. Thus x1 is
very relevant for determining the target value, x2 is of some
relevance, while x3 is irrelevant. The prior over weights is
given by the ARD Gaussian prior with a separate hyper-parameter for
the group of weights associated with each input. A multi-layer
perceptron is trained on this data, with re-estimation of the
hyper-parameters using evidence. The final values for the
hyper-parameters reflect the relative importance of the three inputs.
demmlp1, demev1, mlp, evidenceCopyright (c) Ian T Nabney (1996-9)