I am currently out of office working on a project. As soon as I get home
I will quickly look over your dspam.conf and send you a bunch of
suggestions. Okay?
--
Kind Regards from Switzerland,
Stevan Bajić
On
Fri, 25 Jun 2010 16:15:50 +0200, Norman Uittenbogaart wrote:
Ok thats
not a big problem as this is not really working out.....
Which one should I
use ?
On Fri, Jun 25, 2010 at 3:58 PM, Stevan Bajić wrote:
Hallo
Norman,
getting higher accuracy would require to start from the beginning
since the tokenizer you use is not that intelligent and using anything
other more intelligent would require you to start from the beginning with
the learning.
--
Kind Regards from Switzerland,
Stevan Bajić
On Fri,
25 Jun 2010 15:18:37 +0200, Norman Uittenbogaart wrote:
Hi
Stevan,
Any suggestions to getting the accuracy up would be great !
My
user is shared,managed in the groups file for the domains used
now..
nor...@t*.nl:
TP True Positives: 856
TN True Negatives: 6650
FP
False Positives: 6
FN False Negatives: 2097
SC Spam Corpusfed: 0
NC
Nonspam Corpusfed: 0
TL Training Left: 0
SHR Spam Hit Rate 28.99%
HSR
Ham Strike Rate: 0.09%
PPV Positive predictive value: 99.30%
OCA Overall
Accuracy: 78.11%
On Fri, Jun 25, 2010 at 3:02 PM, Stevan Bajić wrote:
Hallo Norman,
you asked "what is wrong". Right? Nothing is wrong with
your DSPAM installation. There are things you could do better but nothing
is really, really wrong.
Could you post the output of "dspam_stats -H ".
--
Kind Regards from Switzerland,
Stevan Bajić
On Fri, 25 Jun 2010
14:51:30 +0200, Norman Uittenbogaart wrote:
Hello Stevan,
Herewith
enclosed my config.
Kind regards,
Norman
On Fri, Jun 25, 2010 at 2:25
PM, Stevan Bajić wrote:
Hello,
the statistic alone is not enough
information for telling why your accuracy is down. You need to post your
dspam.conf.
--
Kind Regards from Switzerland,
Stevan Bajić
On Fri, 25
Jun 2010 11:29:06 +0200, Norman Uittenbogaart wrote:
I have been
running and training dspam for while now, but it is not at all effective at
the moment.
What could be wrong ?
Since last reset
2083 missed
6
missed
856 caught
6558 delivered
29.126% caught
0.091%
missed
Total processed by filter
2097 missed
6 missed
856
caught
6559 delivered
From corpus
0 fed
0 fed
Overall
accuracy (since last reset)
78.017%
(SPAM messages caught + Good
messages delivered) / Total number of messages
Spam identification
(since last reset)
29.126%
(Spam catch rate only)
Spam ratio (of
total processed)
31.025%
Total SPAM messages (both caught & missed) /
Total number of
message
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