On Tuesday 02 February 2010 15:08:01 Matus UHLAR - fantomas wrote: > On 02.02.10 11:47, Kārlis Repsons wrote: > > in fact, all spam filters are normally designed with an intent to get rid > > of spam, not ham, but anyway, I'm confused with my possible chances to > > miss some mails for no really valid reason. > > _any_ spam filter can have false positives. If there was spam filter that > would have no false positives (and would block all spam), there would be no > spam anymore. If it would not hit any spam, all spammers would change their > spam not to hit that one. > > > I've seen that long list in [1], but that doesn't say much of what should > > be avoided. For example, I remember somewhere it was said, that SpamCop > > may be "too aggressive". > > Spamcop is perfectly good, if properly used. and I think it's perfect even > at SMTP time... > > > So, how should I understand better what to avoid in what cases? (I'd > > rather leave out some dangerous tests and train Bayes filter) > > training bayes filter should help you much. If you notice any false > positives, you can use whitelisting ot increasing the required score.
Well, thanks for replies. Sort of answer I expected, at least, didn't hear any
cries about SpamCop and will enable it.
By the way, I feel interested in scores. For example, I've set up an automatic
sorting, which divides spam into three categories: gray, certain, heavy. I was
looking at that STATISTICS.txt and my first impression about boundaries was:
{4, 6.6, 8}, 4 being the first valid "spam score". However, currently I have
{3, 4, 8}, which might be too drastic for later use, just now when I train
filters and receive no letters, which could easily go as spam. But what would
be your three scalar combination (given, you only wish to personally check
"grey" folder)?
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