  This article considers a semi-supervised classification setting on a Gaussian
mixture model, where the data is not labeled strictly as usual, but instead
with uncertain labels. Our main aim is to compute the Bayes risk for this
model. We compare the behavior of the Bayes risk and the best known algorithm
for this model. This comparison eventually gives new insights over the
algorithm.
