I am still trying to figure out why Bayes is giving so many false positives.
0.000 0 3 0 non-token data: bayes db version 0.000 0 101467 0 non-token data: nspam 0.000 0 39694 0 non-token data: nham 0.000 0 181047 0 non-token data: ntokens 0.000 0 1163102355 0 non-token data: oldest atime 0.000 0 1163306671 0 non-token data: newest atime 0.000 0 1163306671 0 non-token data: last journal sync atime 0.000 0 1163275571 0 non-token data: last expiry atime 0.000 0 172800 0 non-token data: last expire atime delta 0.000 0 30379 0 non-token data: last expire reduction count If I read that right the all of the tokens are from the 9th to the 11th. Is that right? In that case my suggestion to reduce the time is not going to help. But then why has the Bayes locked on to so many bad tokens? I wish there were some way to debug this. Bob
