Bayesian filtering is based on word frequency, or in sophisticated forms, Markov analysis. I'm not confident it could reliably discriminate between useful cate

Bayesian filtering is based on word frequency, or in sophisticated forms, Markov analysis. I'm not confident it could reliably discriminate between useful categories. It'd be more likely to pick up on individuals' different vocabularies than useful categories such as client companies, contracts or projects. To be useful, It'd have to have > 95% accuracy (post training). I'm just not sure a Bayesian model could do that reliably. Unless, of course, it heavily weighted features such as "sender domain", but by that point you might as well be using explicit filters.