Learning (Bayes)

The Bayesian filter learns what your organizations' spam and legitimate mail look like from words, link domains, senders, attachment types and mailer software.

How it learns

• Reports - "Report spam" / "Not spam" on a message page, the Quarantine bulk buttons, and users' portal reports. A report trains the organization's corpus and the shared global corpus.
• Auto-learning - messages scoring 15 or more (not viruses) are learned as spam, clean messages scoring -2 or less as ham, organization corpus only. Switch off in Settings › Bayesian learning.
• Training needs the raw message, so reports only work while a raw copy is retained.
• Reporting the same message again with the opposite label flips it (the old counts are removed).

How it scores

An organization's own counts weigh twice as much as the global corpus, so one client's newsletters don't look like spam to another. Probabilities become rules BAYES_00 to BAYES_99 - see the rule reference.

The Learning page (Protect › Learning)

Corpus

"Global (shared)" plus one row per organization that has trained mail.

Spam / Ham trained

Messages learned of each kind.

Tokens

Distinct features stored.

Status

learning with a progress bar until both counts reach the minimum (50 by default); then active and Bayes starts scoring.