I've been using decibels as a scale for log-odds for a while when reporting results. It works pretty well, since the relevant part of the scale is wide, unlike using nepers, which I had never heard of until I started noodling around with this.
Like, how many decibels of evidence does this observation provide for this hypothesis? That seems potentially pretty workable, as long as you can ensure conditional independence.
Yes. For like a simple naive Bayes, you can say we start at 0, a user vote is worth +3, a merchant vote is +5, we decay by 0.1 every month, publish if we hit +13 (95%), un-publish at +10 (90%), etc. etc.
It's the same math as logits, but the scale's a bit nicer.
