One way would be to consider the true mislabelling rates to follow a certain probability distribution, and caculate the posterior based on the available evidence. Beta distribution again looks like a good candidate, seeing that it can be used to describe the probability of success – “success” meaning a given example being mislabelled, in our case. Again, we will assume uninformative prior, i.e. $$Beta(1,1)$$.