Hi everyone,
I'm a humanities PhD who's been reading Eliezer for a few years, and who's been checking out LessWrong for a few months. I'm well-versed in the rhetorical dark arts, due to my current education, but I also have a BA in Economics (yet math is still my weakest suit). The point is, I like facts despite the deconstructivist tendency of humanities since the eighties. Now is a good time for hard-data approaches to the humanities. I want to join that party. My heart's desire is to workshop research methods with the LW community.
It may break protocol, but I'd like to offer a preview of my project in this introduction. I'm interested in associating the details of print production with an unnamed aesthetic object, which we'll presently call the Big Book, and which is the source of all of our evidence. The Big Book had multiple unknown sites of production, which we'll call Print Shop(s) [1-n]. I'm interested in pinning down which parts of the Big Book were made in which Print Shop. Print Shop 1 has Tools (1), and those Tools (1) leave unintended Marks in the Big Book. Likewise with Print Shop 2 and their Tools (2). Unfortunately, people in the present don't know which Print Shop had which Tools. Even worse, multiple sets of Tools can leave similar Marks.
The most obvious solution that I can see is
If nothing else, this method can define the n-number of Print Shops responsible for the Big Book.
The Bayesian twist on the obvious solution is to add some testing onto the associations, above. Specifically,
find some books strongly associated with Print Shops [x,y,z], in order to
assign probability of patterns of Marks to each Print Shop, then
revise initial associations between Print Shops [x,y,z] and the Big Book proportionally.
I'm far from an expert in Bayesian methods, but it seems already that there's something missing here. Is there some stage where I should take a control sample? Also, how can I find a logical basis for the initial association step, when there are many potential Print Shops? Lastly, how can I account for the decay of Tools, thus increasing Marks, over time?
This is a problem that machine learning can tackle. Feel free to contact me by PM for technical help.
To make sure I understand your problem:
We have many copies of the Big Book. Each copy is a collection of many sheets. Each sheet was produced by a single tool, but each tool produces many sheets. Each shop contains many tools, but each tool is owned by only one shop.
Each sheet has information in the form of marks. Sheets created by the same tool at similar times have similar marks. It may be the case that the marks monotonically increase until the tool is ...
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