## Bayesian Networks MCQ Questions

11. What is needed to make probabilistic systems feasible in the world?

A. Reliability
B. Crucial robustness
C. Feasibility
D. None of the above

12. Where does the bayes rule can be used?

A. Solving queries
B. Increasing complexity
C. Decreasing complexity

13. What does the bayesian network provides?

A. Complete description of the domain
B. Partial description of the domain
C. Complete description of the problem
D. None of the above

14. ____________ is the process of calculating a probability distribution of interest e.g. P(A | B=True), or P(A,B|C, D=True).

A. Diagnostics
B. Supervised anomaly detection
C. Inference
D. Prediction

15. The Distributive law simply means that if we want to marginalize out the variable A we can perform the calculations on the subset of distributions that contain A.

A. TRUE
B. FALSE
C. Can be true or false
D. Can not say

16. Bayesian networks are a factorized representation of the full joint.

A. TRUE
B. FALSE
C. Can be true or false
D. Can not say

17. What is the consequence between a node and its predecessors while creating bayesian network?

A. Functionally dependent
B. Dependant
C. Conditionally independent
D. Both Conditionally dependant & Dependant

18. Which condition is used to influence a variable directly by all the others?

A. Partially connected
B. Fully connected
C. Local connected
D. None of the above

19. To which does the local structure is associated?

A. Hybrid
B. Dependant
C. Linear
D. None of the above

20. When we query a node in a Bayesian network, the result is often referred to as the marginal.

A. TRUE
B. FALSE
C. Can be true or false
D. Can not say