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This is the support site for Andrews & Arnold Ltd, a UK Internet provider. Information on these pages is generally for our customers but may be useful to others, enjoy!

Spam Folder: Difference between revisions

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message to decide whether it is spam or not. One of the
checks it can do, is to compare the message with previous
messages. -this is called Bayesian Learning.
 
==Checking the learning==
If you view the 'headers' of a message, you should see the spam report, and a line looking like:
-3.0 BAYES_00 BODY: Bayes spam probability is 0 to 1%
or perhaps
0.8 BAYES_50 BODY: Bayes spam probability is 40 to 60%
Here you can see the 'Bayes spam probability' as a percentage.
 
==Teaching the system==
If the 'Bayes spam probability' is incorrect, then it can be taught about
If our system is marking non-spam messages as spam, and not marking spam messages, then one way to improce this is
to teach the Bayesian Learning system about messages that have been miss-classified.it Thishas isgot donewrong in the following ways:
 
*Move a message '''OUT''' of the spam folder to tell the system it is '''NOT''' spam
If you make a mistake, just move the message back.
 
The process of learning doesn't guarantee that the system will be correct next time a similar message is received, but it should help.
and you should see a change in the 'probability' in the headers.
 
==Checking the learning==
If you view the 'headers' of a message, you should see the spam report, and a line looking like:
-3.0 BAYES_00 BODY: Bayes spam probability is 0 to 1%
or perhaps
0.8 BAYES_50 BODY: Bayes spam probability is 40 to 60%
Here you can see the 'Bayes spam probability' as a percentage.
 
[[Category:Email Features]]
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