On Saturday, November 09 2013, Karsten Bräckelmann wrote: > Ham is good mail, messages you want (or actually subscribed to), > messages sent to you with your consent. Spam is junk, unsolicited mail > sent to you without your consent. Regardless of SA classification or > score. > > False positives and negatives are messages mis-classified by SA.
On Saturday, November 09 2013, David B. Funk wrote: > For Bayes to work it needs at least 200 examples of Ham (e-mail that > you want) and 200 examples of Spam (e-mail that you don't want). > It doesn't matter if the messages were correctly or not correctly > classified by the rules-based SA engine, just what you consider > Ham/Spam (IE correctly classified by -you-). > In essence you are "teaching" the Bayes system how to recognize > your preferences in e-mail classifying. > > So the messages you've kept in your INBOX should be good for Ham. Nice, thanks both of you for the answers. I am now feeding SA with ham from my INBOX, while I also feed it with false-negatives (interestingly, I am receiving now *much* more spam than I was a week ago...). So, I now have yet another question. I let auto_learn active for SA, and now for every false-negative SA will learn that it is not spam, although it is. I'm now thinking that maybe auto_learn is not a good idea, at least until I have a good enough Bayes database (strangely, SA did not catch *any* spam in the last 48 hours...). Can you confirm this? Thanks a lot, and sorry if I'm asking too much :-). -- Sergio
