bmf is a self contained and extremely efficient Bayesian mail filter. See
Paul Graham's article "A Plan for Spam" for background information. It aims
to be faster, smaller, and more versatile than similar applications.
A Bayesian spam filter for SMTP servers, based on Paul Graham's "A Plan for Spam", http://www.paulgraham.com/spam.html. Includes tools for spam-database maintenance & testing config. parameters. Supports sendmail & postfix; others soon. GPL.
This project applies statistical text categorization techniques to the domain of spam mail filtering. The goal is to produce mail filtering software that can be trained to recognize spam in a particular individual's email. The statistical models produc
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DBNL is a cross-platform library that offers a variety of implementations of Bayesian networks and machine learning algorithms.
It is a flexible library that covers all aspects of Bayesian netwoks from representation to reasoning and learning. It allows you to create simple static networks as well as complex temporal models with changing structure.
It can handle highly non-linear dependencies between multivariate random variables.