handling spammy msgs from legit senders

I occasionally receive commercial messages from legitimate senders using a new FROM name and address. These messages are often very spammy in character. For these situations, is it better not to train Spamsieve so as to avoid improperly biasing the corpus and, instead, add the sender to the whitelist and/or address book and remove the sender header terms from the corpus?

I see what the manual says (below) and recognize this probably isn’t a significant effect, but I’d like to establish a consistent practice that made sense in view of experience to-date.

p. 60 says “it is imperative that you correct SpamSieve when it makes a mistake; otherwise it will “learn” things that aren’t true and begin making predictions based on that incorrect information.” [Similar instructions appear elsewhere.]

I suppose it depends on what you mean by “better.”*Personally, I would tell SpamSieve that the message was good, because I want it to learn to discern the difference between this type of message and actual spam.

But if you want it to treat messages like that as spam—except those from that sender—then I guess it would make sense to let SpamSieve think that the message is spam but to add the address to the whitelist.