We also experimented with a version of IO modified to perform Bayesian MAP estimation, where the Maximization step of the IO procedure is replaced with Bayesian inference using a Dirichlet prior, i.e., where the rule probabilities θ (k) at iteration k are estimated using: Clearly such an approach is very closely related to the Bayesian procedures presented in this article, and in some circumstances this may be a useful estimator.
in our experiments with the Sesotho data above we found that for the small values of α necessary to obtain a sparse solution,the expected rule count E[f r ] for many rules r was less than 1 − α.