 They added common English words to spam messages used for training and testing a spam filter.In two tests they showed that these common words decreased the spam filter's precision (the percentage of messages classified as spam that really are spam) from 84% to 67% and from 94% to 84%.Examining their data shows that the poisoned filter was biased towards believing messages were more likely to be spam than "ham" (good email), thus increasing the false positive rate.