Spam Folder: Difference between revisions

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message to decide whether it is spam or not. One of the
message to decide whether it is spam or not. One of the
checks it can do, is to compare the message with previous
checks it can do, is to compare the message with previous
messages. -this is called Bayesian Learning.
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==
==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. This is done in the following ways:
messages that it has got wrong in the following ways:


*Move a message '''OUT''' of the spam folder to tell the system it is '''NOT''' spam
*Move a message '''OUT''' of the spam folder to tell the system it is '''NOT''' spam
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If you make a mistake, just move the message back.
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.
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]]
[[Category:Email Features]]

Revision as of 12:49, 2 July 2019


When connecting to our email service over IMAP we will create a special folder named spam (lowercase). If you delete the spam folder it will be re-created next time you log in.

The service will then move messages that has been classified as spam in to this folder. This helps keep your inbox free of spam and you should keep an eye on this folder in case there are messages that are not spam.

Our spam checking system performs many checks on a 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

messages that it has got wrong in the following ways:
  • Move a message OUT of the spam folder to tell the system it is NOT spam
  • Move a message IN to the spam folder to tell the system it IS 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.