I don't know the mathematics behind it, but I can say that I've had very good results with SpamBayes for years, during which time spammers' techniques have evolved considerably. One of the strengths of a Bayesian filter is that it gets trained on the messages you actually receive, so it tends to adapt to such changes. (If I don't think it's well-trained for the messages I'm currently receiving, I tend to delete my training database and start fresh, since training is easy and quick.) SpamBayes looks at message headers as well as the message body, and this may help it to correctly classify messages that use tricks in the message bodies.
Bottom line: in my experience, spammers cannot easily get by SpamBayes. Of course, there's no guarantee that this is everyone's experience, or that it will remain true for me forever. One of the odd things about SpamBayes is that it works much better than it seems it should, though, and as long as that's the case, I plan to keep using it. -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of gpr Sent: Wednesday, December 19, 2007 1:18 PM To: spambayes@python.org Subject: [Spambayes] Can spammers easily sneak through the SpamBayes filter ? Can spammers easily sneak through the SpamBayes statistical filters easily - for example how about a spam message with good words camouflaged (in something like white color) and only spam content visible to the user. When the filter comes across the message the spam score would lean towards lower value and would sneak through the filter. How does SpamBayes address such spam techniques? Thank you, Ram -- View this message in context: http://www.nabble.com/Can-spammers-easily-sneak-through-the-SpamBayes-fi lter---tp14422190p14422190.html Sent from the Spambayes - General mailing list archive at Nabble.com. _______________________________________________ SpamBayes@python.org http://mail.python.org/mailman/listinfo/spambayes Info/Unsubscribe: http://mail.python.org/mailman/listinfo/spambayes Check the FAQ before asking: http://spambayes.sf.net/faq.html _______________________________________________ SpamBayes@python.org http://mail.python.org/mailman/listinfo/spambayes Info/Unsubscribe: http://mail.python.org/mailman/listinfo/spambayes Check the FAQ before asking: http://spambayes.sf.net/faq.html
