  In this article we select the unknown dimension of the feature by re-
versible jump MCMC inside a simulated annealing in bayesian set up of
collaborative filter. We implement the same in MovieLens small dataset. We also
tune the hyper parameter by using a modified empirical bayes. It can also be
used to guess an initial choice for hyper-parameters in grid search procedure
even for the datasets where MCMC oscillates around the true value or takes long
time to converge.
