I've heard to try for equal numbers of spam training and ham training.
I've used the defaults for autolearn, and manually relearned all the false
positives. It seems that learning the false negatives would be a good thing
too, but dump magic is already way over 10:1 spam.
Do I need to do something different?
Dan
3 0 non-token data: bayes db version
1402564 0 non-token data: nspam
119267 0 non-token data: nham
151248 0 non-token data: ntokens
1179379647 0 non-token data: oldest atime
1179466091 0 non-token data: newest atime
0 0 non-token data: last journal sync atime
1179466101 0 non-token data: last expiry atime
86400 0 non-token data: last expire atime delta
44795 0 non-token data: last expire reduction count
