Dallas Engelken wrote: > Ok, Lets take the following sample data.... > > Email: 2766 > Spam: 975 > Ham: 1791 > > TOP SPAM RULES FIRED > ---------------------------------------------------------------------- > RANK RULE NAME COUNT %OFMAIL %OFSPAM %OFHAM > ---------------------------------------------------------------------- > 7 HTML_MESSAGE 629 22.74 64.51 34.51 > ---------------------------------------------------------------------- > > TOP HAM RULES FIRED > ---------------------------------------------------------------------- > RANK RULE NAME COUNT %OFMAIL %OFSPAM %OFHAM > ---------------------------------------------------------------------- > 6 HTML_MESSAGE 618 22.34 64.51 34.51 > ---------------------------------------------------------------------- > > we had 2766 total emails. > > for %OFMAIL, > 629 spam messages hit HTML_MESSAGE which is 629/2766 = 22.74%. > 618 ham messages hit HTML_MESSAGE which is 618/2766 = 22.34%.
Oh, I see now. Thanks for clearing that up. So the correct interpretation is that 22.74% of mail is "HTML spam", and 22.34% of mail is "HTML ham". Adding the two together, 45.08% of mail matches HTML_MESSAGE (for this sample data.) -- Matthew.van.Eerde (at) hbinc.com 805.964.4554 x902 Hispanic Business Inc./HireDiversity.com Software Engineer
