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Reply-To: "Jonathan Nichols" <jnichols@pbp.net>
From: "Jonathan Nichols" <jnichols@pbp.net>
To: "Fox" <lds0062@cdc.net>, <razor-users@example.sourceforge.net>
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Subject: Re: [Razor-users] Razor v2 effectiveness stats - HTML table - Take 2
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Oh, I was serious. I'm awful with perl/etc. I just think the HTML graph that
was created was pretty neat and I wish I could do something like that. :-)


> I can't tell if you are serious or joking.  I have a custom perl based
spam
> blocking framework that uses plug-ins to block spam.  I test each message
> with every plug-in and keep the stats in a mysql database, which are what
> you see below.
>
> Fox
>
>
> ----- Original Message -----
> From: "Jonathan Nichols" <jnichols@pbp.net>
> To: <razor-users@example.sourceforge.net>
> Sent: Tuesday, September 03, 2002 2:07 PM
> Subject: Re: [Razor-users] Razor v2 effectiveness stats - HTML table -
Take
> 2
>
>
> > How do you make up graphs like that, anyway? :-)
> >
> > ----- Original Message -----
> > From: "Daniel Higgins" <dhiggins@netc.net>
> > To: "Fox" <lds0062@cdc.net>; <razor-users@example.sourceforge.net>
> > Sent: Tuesday, September 03, 2002 10:57 AM
> > Subject: Re: [Razor-users] Razor v2 effectiveness stats - HTML table -
> Take
> > 2
> >
> >
> > that's pretty impressive, have you seen any false positives yet? myself
> i'm
> > still at the stage of creating the corpuses. i'll report back after i
get
> > some testing of my own :P
> >   ----- Original Message -----
> >   From: Fox
> >   To: razor-users@example.sourceforge.net
> >   Sent: Tuesday, September 03, 2002 12:54 PM
> >   Subject: Re: [Razor-users] Razor v2 effectiveness stats - HTML table -
> > Take 2
> >
> >
> >   Sorry about the html, for those of you still using elm or other
non-GUI
> >   clients.  I don't have time to post it as text.
> >
> >   The "Spam Count" is the total of all spam detected by the various
> filters.
> >
> >   Jammed is a custom phrase ranking system.
> >   Razored is Razor v2.
> >   Bayesian filter is based off of Paul Graham's work (statistical
> >   probability), using a corpus of 4000 non-spam and 2000 spam messages.
> >
> >         Spam Statistics
> >         Date Spam Count Jammed Razored Blacklisted Trollbox Bayesian
> >         2002-08-27 370 145    (39.19%) 181    (48.92%) 79    (21.35%)
120
> > (32.43%) 275    (74.32%)
> >         2002-08-28 397 106    (26.70%) 126    (31.74%) 163    (41.06%)
136
> > (34.26%) 320    (80.60%)
> >         2002-08-29 346 154    (44.51%) 146    (42.20%) 78    (22.54%)
101
> > (29.19%) 261    (75.43%)
> >         2002-08-30 366 163    (44.54%) 166    (45.36%) 65    (17.76%)
138
> > (37.70%) 272    (74.32%)
> >         2002-08-31 282 211    (74.82%) 133    (47.16%) 27    ( 9.57%)
132
> > (46.81%) 256    (90.78%)
> >         2002-09-01 220 127    (57.73%) 125    (56.82%) 22    (10.00%) 91
> > (41.36%) 157    (71.36%)
> >         2002-09-02 166 86    (51.81%) 77    (46.39%) 22    (13.25%) 64
> > (38.55%) 123    (74.10%)
> >
> >
> >
> >
> >
> >
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