http://3cbzkrvakrpetjjppdwzbzqrlkmzatjs7jbyazap5gwutj32gcltjpqd.onion
So, those labels need to be excluded,
or the small sample sizes wreck the training feedback loop.
Currently, I have ten active labels, and even though the point
of this is not to be a spam filter, “spam” is one of the labels. Out of curiosity, I decided to compare the performance of
my three different models, and to do so on a neutral corpus
(in other words, emails that none of them had ever been
trained on).