On 1/15/2013 4:05 PM, Bowie Bailey wrote: > On 1/15/2013 3:47 PM, Ben Johnson wrote: >> One final question on this subject (sorry...). >> >> Is there value in training Bayes on messages that SA classified as spam >> *due to other test scores*? In other words, if a message is classified >> as SPAM due to a block-list test, but the message is new enough for >> Bayes to assign a zero score, should that message be kept and fed to >> sa-learn so that Bayes can soak-up all the tokens from a message that is >> almost certainly spam (based on the other tests)? >> >> Am I making any sense? > > It is always worthwhile to train Bayes. In an ideal world, you would > hand-sort and train every email that comes through your system. The > more mail Bayes sees the more accurate it can be. >
Thanks, Bowie. Given your response, would it then be prudent to call "sa-learn --spam" on any message that *other tests* (non-Bayes tests) determine to be spam (given some score threshold)? The crux of my question/point is that I don't want to have to feed messages that Bayes "misses" but that other tests identify *correctly* as spam to "sa-learn --spam". Is there value in implementing something like this? Or is there some caveat that would make doing so self-defeating? Thanks a bunch, -Ben
