How are the scores assigned?

Wiki MarkupThe scores are assigned using a neural network trained with error back propagation (\["Perceptron"\]). Both systems attempt to optimise optimize the efficiency of the rules that are run in terms of minimizing the number of false positives and false negatives. Wiki MarkupA list of the rules and their assigned scores is at \[http://spamassassin.apache.org/tests.html tests\].

You can find all of the currently active rules and their scores in the Subversion repository under /trunk/rules or by downloading the latest published set using the sa-update tool. 

You can help this system by providing statistics on your mail spool via NightlyMassCheck and RescoreMassCheck.

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Confusing

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scores

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Scores for "learn" rules (example the various BAYES_?? rules) are scored using the same method. This can produce scores which seem incorrect (example BAYES_80 with a higher score than BAYES_99). This is due to the fact that rules are not related to one another, they're separate rules have separate scores.

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A score of 0 will stop a rule from being run.

In version 2.x, the scores are assigned using a genetic algorithm (GA).