Werkgemeenschap voor Informatie- en Communicatietheorie (WIC)
Abstract
The Universal Modeling algorithms proposed in [2] for two general classes of finite-context sources are reviewed. The above methods were constructed by viewing a model structure as a partition of the context space and realizing that a partition can be reached through successive splits. Here we start by constructing recursive counting algorithms to count all models belonging to the two classes and use the algorithms to perform the Bayesian Mixture. The resulting methods lead to computationally more efficient Universal Modeling algorithms
