Latent Dirichlet Allocation and Bayes Thereom

Bayesian Filtering - Uses a Naive Bayes Classifier to determine the likelihood of an email being spam or non-spam based upon the statistical likelihood of tokens in the email. In probability theory and statistics, Bayes' theorem (alternatively Bayes' law) is a theorem with two distinct interpretations. In the Bayesian interpretation, it expresses how a subjective degree of belief should rationally change to account for evidence. In the frequentist interpretation, it relates inverse representations of the probabilities concerning two events. In the Bayesian interpretation, Bayes' theorem is fundamental to Bayesian statistics, and has applications in fields including science, engineering, economics (particularly microeconomics), game theory, medicine and law. The application of Bayes' theorem to update beliefs is called Bayesian inference. Good explanation of Bayes Thereom along with an example. http://en.wikipedia.org/wiki/Bayes%27_theorem Still not 100% sure how Latent Dirichlet Allocation is related to Bayesian Filtering? http://en.wikipedia.org/wiki/Latent_Dirichlet_allocation