Bayesian models are based on Bayes' theorem from 1812. Bayes' theorem describes the probability that an event will occur based on prior knowledge of the system. For example, what is the probability that a machine will fail based on the temperature of the device?
Bayes' theorem is expressed as:
A and B are the events of interest. P(A|B) asks, what is the probability that event A will occur, given event B has occurred? They have no relation to each other, and are mutually exclusive.
The equation can be re-written using the theorem of total probability, which replaces P(B). We can also extend this to i number of events.
