Training SpamAssassin to spot spam emails involves giving it lots of examples of spam and non-spam (ham) emails. First, you collect emails and manually mark them as either spam or ham. SpamAssassin uses this information to learn what spam looks like using something called Bayesian learning. The more examples you give, the better it gets at telling spam from ham.
Besides learning from examples, SpamAssassin uses other methods like network tests and rules that look for common spam traits. It can also use shared data from other users to improve its accuracy. Regularly updating and adjusting these rules helps SpamAssassin stay effective as spammers change their tactics. This way, SpamAssassin gets better at catching spam and reducing mistakes where it might mark good emails as spam. https://docs.google.com/drawings/d/1TrIPkoDcb6LXhVWZkUUHx0w76VE2PeKHNJw7-pkpijQ/ https://docs.google.com/presentation/d/18oL1ejhDOYEcUrRyl7JMo1FvCwUrIBCw69Mlc8L6nV4/edit?usp=sharing https://docs.google.com/forms/d/e/1FAIpQLSf8NFrdWpqPnDxCDhhLm4OmrcVEKfP3IgqEpxpcfipWIhCAwA/viewform https://sites.google.com/view/mybacklinksstock/home https://taplink.cc/jenniferlily https://buyandsellhair.com/author/jenniferlily/ _______________________________________________ Isbg mailing list -- isbg@python.org To unsubscribe send an email to isbg-le...@python.org https://mail.python.org/mailman3/lists/isbg.python.org/ Member address: arch...@mail-archive.com
