> > Now that I've straightened out my sa-learn script, I've stopped getting
> > BAYES__ and false positives. The problem is that I've also stopped getting
> > any Bayes hits at all.
> >
> > I've put a heckuvalot of spam/ham through the learning process. Is there
> > any easy way to check if I've hit the threshold yet? I used:
> >
> > sa-learn --dump
> >
> > but I have no idea what its telling me.
>
> Just use sa-learn --dump magic
>
> For example I get:
>
> sa-learn --dump magic
> 0.000 0 2 0 non-token data: bayes db version
> 0.000 0 281989 0 non-token data: nspam
> 0.000 0 99372 0 non-token data: nham
> 0.000 0 172696 0 non-token data: ntokens
> 0.000 0 1064978900 0 non-token data: oldest atime
> 0.000 0 1065038943 0 non-token data: newest atime
> 0.000 0 1065038857 0 non-token data: last journal sync
> atime
> 0.000 0 1065022142 0 non-token data: last expiry atime
> 0.000 0 43200 0 non-token data: last expire atime
> delta
> 0.000 0 94019 0 non-token data: last expire
> reduction count
>
> Which is saying that 281989 spam's are learn't and 99372 hams..
>
> Regards,
> Simon
Now I'm really really confused. I wiped the Bayes database and did a
spam/ham learning run. Here is the output from sa-learn.
Learned from 13 message(s) (13 message(s) examined).
Learned from 121 message(s) (121 message(s) examined).
Learned from 274 message(s) (274 message(s) examined).
Learned from 717 message(s) (717 message(s) examined).
Learned from 126 message(s) (126 message(s) examined).
Learned from 106 message(s) (106 message(s) examined).
Learned from 331 message(s) (331 message(s) examined).
synced Bayes databases from journal in 1380 seconds: 329773 unique entries
And here is the output from my "sa-learn --dump magic"
0.000 0 2 0 non-token data: bayes db version
0.000 0 1 0 non-token data: nspam
0.000 0 0 0 non-token data: nham
0.000 0 116 0 non-token data: ntokens
---snip---
Its as if the only updates were from auto-learn. What am I missing?
--
Jack Gostl [EMAIL PROTECTED]
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