If I have a list of outcomes to a scenario like:
(Fast / Slow), (close to home / far from home), (car, truck), (daytime / nighttime)
and a list of outcomes:
Slow / Close to Home / Car / Daytime
Fast / Far From Home / Truck / Nighttime
Slow / Close to Home / Car / Nighttime
Fast / Close to Home / Truck / Daytime
Slow / Close to Home / Car / Daytime
And I wanted to create something similar to a Bayesian Belief Network where I could say, 'Given that it was far from home, what is the probability it was each of Slow / Fast / Car / Truck / Daytime, what would be the best way to create a formula to provide this output?
I am familiar with Bayesian Belief Networks, but I would imagine there are other ways to create this formula, preferably in python. Is there an accepted technique for creating this sort of a function that is easy to reproduce algorithmically? My issue is BBN's are bulky and I'm not very familiar with setting them up algorithmically from a given input.
If BBN is the best solution, what is the preferred technique for establishing one?