A Posterior Distribution for Anti-Spam Bayesian Statistical Model

This paper deals with Bayesian models applied to anti-spam. In our previous work involved in mathematically modeling the behavior of spam, we worked on defining the priors distributions that summarize the behavior of spam. In this paper, taking into account certain priors distributions and we define the posterior distributions that summarize the probability that a received message is spam. These laws a priori and a posteriori certainly help improve the spam detection and increase the reliability decision.