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

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12. Where does the bayes rule can be used?

A. Solving queries
B. Increasing complexity
C. Decreasing complexity
D. Answering probabilistic query

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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

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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 

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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

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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

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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

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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

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19. To which does the local structure is associated?

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

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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

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