I have just such a thing, referred to as “Marks.” I haven’t yet included that in the code, because I wanted to explore the viability of the method first. So to retreat to the earlier question, why does my proposal strike you as a GIGO situation?
So to retreat to the earlier question, why does my proposal strike you as a GIGO situation?
You claimed to not know what printers there were, how many there were, and what connection they had to ‘Marks’. In such a situation, what on earth do you think you can infer at all? You have to start somewhere: ‘we have good reason to believe there were not more than 20 printers, and we think the London printer usually messed up the last page. Now, from this we can start constructing these phylogenetic trees indicating the most likely printers for our sample of books...’ There is no view from nowhere, you cannot pick yourself up by your bootstraps, all observation is theory-laden, etc.
This all sounds good to me. In fact, I believe that researchers in the humanities are especially (perhaps overly) sensitive to the reciprocal relationship between theory and observation.
I may have overstated the ignorance of the current situation. The scholarly community has already made some claims connecting the Big Book to Print Shops [x,y,z]. The problem is that those claims are either made on non-quantitative bases (eg, “This mark seems characteristic of this Print Shop’s status.”) or on a very naive frequentist basis (eg, “This mark comes up N times, and that’s a big number, so it must be from Print Shop X”). My project would take these existing claims as priors. Is that valid?
I have no idea. If you want answers like that, you should probably go talk to a statistician at sufficient length to convey the domain-specific knowledge involved or learn statistics yourself.
I don’t understand what this means. Can you say more?
http://en.wikipedia.org/wiki/Feature_%28machine_learning%29 A specific concrete variable you can code up, like ‘total number of commas’.
I have just such a thing, referred to as “Marks.” I haven’t yet included that in the code, because I wanted to explore the viability of the method first. So to retreat to the earlier question, why does my proposal strike you as a GIGO situation?
You claimed to not know what printers there were, how many there were, and what connection they had to ‘Marks’. In such a situation, what on earth do you think you can infer at all? You have to start somewhere: ‘we have good reason to believe there were not more than 20 printers, and we think the London printer usually messed up the last page. Now, from this we can start constructing these phylogenetic trees indicating the most likely printers for our sample of books...’ There is no view from nowhere, you cannot pick yourself up by your bootstraps, all observation is theory-laden, etc.
This all sounds good to me. In fact, I believe that researchers in the humanities are especially (perhaps overly) sensitive to the reciprocal relationship between theory and observation.
I may have overstated the ignorance of the current situation. The scholarly community has already made some claims connecting the Big Book to Print Shops [x,y,z]. The problem is that those claims are either made on non-quantitative bases (eg, “This mark seems characteristic of this Print Shop’s status.”) or on a very naive frequentist basis (eg, “This mark comes up N times, and that’s a big number, so it must be from Print Shop X”). My project would take these existing claims as priors. Is that valid?
I have no idea. If you want answers like that, you should probably go talk to a statistician at sufficient length to convey the domain-specific knowledge involved or learn statistics yourself.