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Comment: Added IMAP training section

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#Uncomment the following lines and use tail -f procmail.log to debug
#LOGFILE=$HOME/procmail.log
#VERBOSE=yes
#LOGABSTRACT=all

# Feed redirected spam to sa-learn, and also store a copy in a folder called spam.
# This folder of false negatives could be useful if we needed to rebuild our Bayes
# database in the future.

:0
* ^To:.*spam@example.com
* < 256000

   {
   :0c: spamassassin.spamlock
   | sa-learn --spam

   :0: spamassassin.filelock
   spam
   }

# Send all other mail through SpamAssassin

:0fw: spamassassin.lock
* < 256000
| spamassassin


# Mail that is very likely spam (>15) can be saved on the server
# (not forwarded), or by moving the # down one line, even dropped
# on the floor.  Note that dropping mail on the floor is a *bad*
# idea unless you really, really believe no false positives will
# have a score greater than 15.  If you want all mail forwarded,
# just add #'s in front of each of these lines:

:0: spamassassin.filelock2
* ^X-Spam-Level: \*\*\*\*\*\*\*\*\*\*\*\*\*\*\*
#/dev/null
almost-certainly-spam


# Forward all mail with a score less than 15 to my non-publicized address 
:0
! privateaddress@example.net

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Way more detail on how to do this is at SingleUserUnixInstall.

Other training options

Wiki Markup
An even easier form of mistake-based training is to use IMAP and create a Learn{{`As}}`Spam folder, as described in the
\[wiki:Self:SingleUserUnixInstall#head-bea6b8dc4f219edd3b9976e8f922a8f1c0603125 IMAP section of SingleUserUnixInstall\].

Contributors

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CategoryBayes