‘No free lunches’, right? If you’re getting anything out of your unsupervised methods, that just means they’re making some sort of assumptions and proceeding based on those.
Sorry to interrupt a perfectly lovely conversation. I just have a few things to add:
I may have overstated the case in my first post. We have some information about print shops. Specifically, we can assign very small books to print shops with a high degree of confidence. (The catch is that small books don’t tend to survive very well. The remaining population is rare and intermittent in terms of production date.)
There are some hypotheses that could be treated as priors, but they’re very rarely quantified (projects like this are rare in today’s humanities).
Not quite. You can get quite a bit of insight out of unsupervised clustering.
‘No free lunches’, right? If you’re getting anything out of your unsupervised methods, that just means they’re making some sort of assumptions and proceeding based on those.
Right, but this isn’t a free lunch so much as “you can see a lot by looking.”
Sorry to interrupt a perfectly lovely conversation. I just have a few things to add:
I may have overstated the case in my first post. We have some information about print shops. Specifically, we can assign very small books to print shops with a high degree of confidence. (The catch is that small books don’t tend to survive very well. The remaining population is rare and intermittent in terms of production date.)
There are some hypotheses that could be treated as priors, but they’re very rarely quantified (projects like this are rare in today’s humanities).