> The hard part here is to detect false assumptions from users. For example,
> some
> will say that a mail is a spam while it is not, it is just a mailing list
> from a
> shop where they bought a product and clicked on the "I want to receive your
> mailings". The reverse is also possible (think phishing). As strange as it may
> sound, "un-spam-educated" users are often less accurate than automated spam
> filters.
Yes. Even trained eyes can make mistakes when sorting spam/innocent.
Anyways, you can fork a random sample of the messages, lets say 1% to a
spam counting mailbox:
#------------------------
# fork a random sample of the messages
#------------------------
random_sample:
driver = redirect
local_part_suffix = +*
local_part_suffix_optional
condition = ${if eq {${eval:($tod_epoch+$pid)%100}}{0} {yes}{no} }
data = [EMAIL PROTECTED]
redirect_router = next_router_after_sampler
unseen
no_verify
#------------------------
Make sure the curly brackets are correct.
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