Re: New user and question
Thomas Anderson <[email protected]>
| Newsgroups | gmane.mail.bogofilter.general |
|---|---|
| Organization | Order amid Chaos |
| Message-ID | <[email protected]> |
On 10/25/2010 6:57 PM, RW wrote: > On Mon, 25 Oct 2010 16:03:32 -0400 > Thomas Anderson<[email protected]> wrote: >> I recommend training to exhaustion. That is, when a false positive, >> false negative, or unsure shows up, first you train it, then you >> check it again as if the same exact email arrived another time, and >> if it still doesn't classify correctly, train it again -- repeat >> until it classifies correctly. > > In my my experience that's ineffective with default settings because the > influence of new hapaxes and low-count tokens virtually guarantees > correct identification on the second test - unless you use a very large > value of "robs" that would be unsuitable for normal classification. It > makes more difference if you do it iteratively on corpora. I've had great success doing it this way. These are my settings: robx=0.69 robs=0.33 min_dev=0.2 spam_cutoff=0.7 ham_cutoff=0.3 The method may indeed be less necessary for small word lists. But by the time you've had a few tens of thousands of emails through bogofilter, a single training often has little effect. Doing the exhaustive training method ensures that your manual indication that a given email is ham or spam is actually reflected in subsequent classifications. That said, I would use the method even if starting from a brand spanking new word list since there is no cost in doing so and the beneficial effect may be noticeable fairly quickly. BTW, I would amend my initial response to advise the original poster, Doug, to also set his spam_cutoff a little lower in order to capture more spammy unsures as spam. But to prevent false positives, robx should always be less than spam_cutoff. Tom _______________________________________________ Bogofilter mailing list [email protected] http://www.bogofilter.org/mailman/listinfo/bogofilter