That’d be interesting. More posts on the real world use of bayesian models would be good for lesswrong I think.
But I’m not sure how relevant to my problem. I’m in the process of writing up my design deliberations and you can judge better once you have read them.
The reason I say that our problems are related is that inferring the relevant properties of a sensor’s likelihood function looks like a standard case of finding out how the probability distribution clusters. Your problem, that of identifying a file type from its binary bitstream, is doing something similar—finding what file types have what PD clusters.
That’d be interesting. More posts on the real world use of bayesian models would be good for lesswrong I think.
But I’m not sure how relevant to my problem. I’m in the process of writing up my design deliberations and you can judge better once you have read them.
Looking forward to it!
The reason I say that our problems are related is that inferring the relevant properties of a sensor’s likelihood function looks like a standard case of finding out how the probability distribution clusters. Your problem, that of identifying a file type from its binary bitstream, is doing something similar—finding what file types have what PD clusters.