I basically determine p via Bayesian inference within every bin (via a conjugate beta prior for p which gives a beta posterior). If that’s not Bayesian then I don’t know what is :)
Yes the pruning can be done with a frequentist method too. Yes you can come up with smarter / more statistically sound ways to construct these binnings. Do they work on >1e9 data points?
Yes the pruning can be done with a frequentist method too. Yes you can come up with smarter / more statistically sound ways to construct these binnings. Do they work on >1e9 data points?