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This does not make any sense to me and neither did OP's comment about NN's approximating the posterior. In fact, if p were the solution then that would simply
by beta_binomial 8y ago
This does not make any sense to me and neither did OP's comment about NN's approximating the posterior. In fact, if p were the solution then that would simply be the maximum likelihood estimate, which would not include the p(theta), or the prior, and hence would not be Bayesian.
- cosmic_ape 8y agoWell, p definitely is the solution in the case I mentioned. It is indeed the maximum likelihood solution. You could incorporate prior info about theta via a regularization term, if so inclined. What does not make sense in this? Not sure what the OP meant, but I though it might be useful to mention how estimators may be interpreted as anything probabilistic at all. Often, arbitrary numbers between 0 and 1 are termed "probabilities", but in this case there actually is some proportion or probability to which f(x) should ideally correspond.