Re: generating rule stats from spamd logs

[Steve Martin]

He only fixed the spam rules section. The TOP HAM RULES sections still has these two incorrect computations...     my $perc2=sprintf("%.2f",($HAM_RULES{$key}/$NUM_SPAM)*100);     my $perc3=sprintf("%.2f",($SPAM_RULES{$key}/$NUM_HAM)*100); Number of times a rule fired on ham / total number of spam messages. Number of times a rule fired on spam / total number of ham messages.     my $perc2=sprintf("%.2f",($SPAM_RULES{$key}/$NUM_SPAM)*100);     my $perc3=sprintf("%.2f",($HAM_RULES{$key}/$NUM_HAM)*100); On Jul 27, 2005, at 11:32 AM, Andy Jezierski wrote: "Dallas L. Engelken" <[EMAIL PROTECTED]> wrote on 07/27/2005 11:26:54 AM: >  > -----Original Message----- > > From: Chris Thielen [mailto:[EMAIL PROTECTED]] > > Sent: Wednesday, July 27, 2005 11:02 AM > > To: Dallas L. Engelken > > Cc: users@spamassassin.apache.org > > Subject: Re: generating rule stats from spamd logs > > > > Dallas L. Engelken wrote: > > > > >BAYES_00 hits 15.27 of spam on yours, the %ofspam on top ham > > rules and > > >%ofham on top spam rules must be buggy. > > > > > >i'm not running that version with the 5th column.   It must be buggy. > > >i play with it after bit. > > > > > >Dallas > > >   > > > > > > > Dallas, > > > > Did you see the patch I sent to the SARE list?  Just need to > > swap two hash lookups. > > > > > > Yup yup.  http://www.rulesemporium.com/programs/sa-stats.txt updated. > > D Something's still a little fishy.  SA 3.1 latest SVN, if it makes any difference. python# ./sa-stats -f maillog.0 -n 5 Email:     6111  Autolearn:   226  AvgScore:   2.15  AvgScanTime:  3.91 sec Spam:       655  Autolearn:   133  AvgScore:  14.81  AvgScanTime:  3.76 sec Ham:       5456  Autolearn:    93  AvgScore:   0.63  AvgScanTime:  3.93 sec Time Spent Running SA:         6.64 hours Time Spent Processing Spam:    0.68 hours Time Spent Processing Ham:     5.96 hours TOP SPAM RULES FIRED ------------------------------------------------------------ RANK    RULE NAME                       COUNT %OFRULES %OFMAIL %OFSPAM  %OFHAM ------------------------------------------------------------    1    HTML_MESSAGE                      496     5.67    8.12   75.73   62.19    2    DCC_CHECK                         310     3.55    5.07   47.33    7.02    3    BAYES_99                          305     3.49    4.99   46.56    0.02    4    RAZOR2_CHECK                      277     3.17    4.53   42.29    4.23    5    DIGEST_MULTIPLE                   251     2.87    4.11   38.32    2.42 ------------------------------------------------------------ TOP HAM RULES FIRED ------------------------------------------------------------ RANK    RULE NAME                       COUNT %OFRULES %OFMAIL %OFSPAM  %OFHAM ------------------------------------------------------------    1    BAYES_00                         4079    14.05   66.75  622.75    1.83    2    HTML_MESSAGE                     3393    11.68   55.52  518.02    9.09    3    NO_REAL_NAME                     1053     3.63   17.23  160.76    1.06    4    HTML_80_90                        931     3.21   15.23  142.14    2.35    5    LG_4C_2V_3C                       798     2.75   13.06  121.83    2.20 ------------------------------------------------------------   -- Steve Martin                              http://www.cheezmo.com/ Smart Calibration, LLC           http://www.smartcalibration.com/ The Widescreen Movie Center            http://www.widemovies.com/ Letterboxed Movie TV Schedule  http://www.widemovies.com/lbx.html