Right now in SA 4.0.1 bayes at least for me is really challenging to train and set up.
I had good trained DB from past V3 install, and it behaved really odd. I trained it on new set of mails 3000 spam and 3000 ham (HAND PICKED mail it was PAIN) and I cant get either BAYES_00 or BAYES_99 :) I mean I get them occasionally, but not even close to what it was in V3. In V3 SA bayes was decisive, when well trained it was awesome. Nov in V4.0.1 bayes is NON decisive, and in 90% of cases it gives me BAYES_40 or _50 even after I mark those mails as SPAM OR HAM. What is even more weird is, that some mails aren`t even bayes scored at all. BAYES_XX is missing from headers entirely and I don`t know why... I`m kind of sorry that I upgraded to 4.0.1... Regards,G ________________________________ From: Alex <mysqlstud...@gmail.com> Sent: Tuesday, 17 September 2024 22:29 To: SA Mailing list Subject: Re: Tips on training bayes? It is up to the user, ie you, what is and what is not spam. Well, yes, and no. Of course it's my own system and I can define these terms however I wish. I'm also familiar with the need to investigate every message - perhaps I should have made that clear initially. It's only these few types of messages that are very subjective and experience from the broader open source community would be appreciated. If it has a legitimate unsubscribe link, does that make it ham? What criteria do you use to determine "spamminess/haminess of EVERY message"? Is the goal to have every message one of either BAYES_00 or BAYES_99 or is it okay that newsletters (for example) are BAYES_50, and let other rules, like network checks, determine the score? Thanks, Alex
