In Bayes/​Pearl terminology, knowledge of an effect destroys the causes’ independence (d-connects them), and ruling out a cause shifts probability onto the remaining causes.
How does a Bayesian rule out a cause?
In Bayes/​Pearl terminology, knowledge of an effect destroys the causes’ independence (d-connects them), and ruling out a cause shifts probability onto the remaining causes.
How does a Bayesian rule out a cause?