On Sun, 2006-06-25 at 16:51 -0400, Claude Jones wrote: > After the big discussion a month or so ago, I decided to give spamassassin > another fair try - this prompted by my having created self-imposed problems > getting spambayes to work on my home FC5 pc. I use kmail - supposedly, kmail > detects spamassassin and give you the option of configuring/using it - it > provides training buttons on the menu-bar, so you can go through your inbox > and separate the spam; I also trained on a number of ham messages that had > been filtered into various folders, training on several from each folder. > After intially terrible results, my spam detection crept up to about 80%. > Since I get over 200 spam messages daily, that still would leave over 40 > messages to sift through daily, not so great. Today, I finally got Spambayes > running; after initial training on about 200+ messages, I'm already getting > around 95% spam detection... > > Am I missing something here? Is there a better way to train spamassassi Some people find it helpful to change the BAYES_99 test to me equal to the spam cutoff or slightly below it. If the spam cutoff value is 5.0, set BAYES_99 test value is set at 5.0 or 4.9. Another philosophy suggests to periodically retrain spamassassin on spam that has already been identified as such by spamassassin. There are many other spamassassin tests you can fool with. Look at :http://lwn.net/Articles/172491/ and you will see when tested spamassassin beats spambayes in spam identification. I don't want any flame wars on this but I stick to my assertion that when used properly spamassassin is philosophically either equal or slightly better than spambayes in detecting spam. That is, spambayes's approach is no better than spamassassin so I would expect comparable results. -- ======================================================================= The IBM purchase of ROLM gives new meaning to the term "twisted pair". -- Howard Anderson, "Yankee Group" ======================================================================= Aaron Konstam telephone: (210) 656-0355 e-mail: akonstam@xxxxxxxxxxxxx
