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- a)
- [1 P] Construct a Bayesian network which represents the conditional independence assumptions
of the probability distributions from example 1 and 2.
- b)
- [2 P] Construct two different Bayesian network which encodes exactly the following conditional independence assumptions
- c)
- [2 P] A doctor gives a patient a drug dependent on their age and gender. The patient has a probability to recover
depending on whether s/he receives the drug, how old s/he is and which gender the patient has. Additionally
it is known that age and gender are conditional independent if nothing else is known from the patient.1
- (i)
- Draw the Bayesian network which describes this situation.
- (ii)
- How does the factorized probability distribution look like?
- (iii)
- Write down the formula to compute the probability that a patient recovers given that you know
if s/he gets the drug. Write down the formula using only probabilities which are part of
the factorized probability distribution.
Next: d-separation
Up: MLA_Exercises_2013
Previous: Conditional Independence
Hubner Florian
2014-01-21