1. How many terms are required for building a Bayesian model?

a) 1

b) 2

c) 3

d) 4

View Answer

Explanation: The three required terms are a conditional probability and two unconditional probability.

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

a) Reliability

b) Crucial robustness

c) Feasibility

d) None of the mentioned

View Answer

Explanation: On a model-based knowledge provides the crucial robustness needed to make probabilistic system feasible in the real world.

3. Where does the Bayes rule can be used?

a) Solving queries

b) Increasing complexity

c) Decreasing complexity

d) Answering probabilistic query

View Answer

Explanation: Bayes rule can be used to answer the probabilistic queries conditioned on one piece of evidence.

4. 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 mentioned

View Answer

Explanation: A Bayesian network provides a complete description of the domain.

a) Using variables

b) Using information

c) Both a & b

d) None of the mentioned

View Answer

Explanation: Every entry in the full joint probability distribution can be calculated from the information in the network.

6. How the Bayesian network can be used to answer any query?

a) Full distribution

b) Joint distribution

c) Partial distribution

d) All of the mentioned

View Answer

Explanation: If a Bayesian network is a representation of the joint distribution, then it can solve any query, by summing all the relevant joint entries.

7. How the compactness of the Bayesian network can be described?

a) Locally structured

b) Fully structured

c) Partial structure

d) All of the mentioned

View Answer

Explanation: The compactness of the Bayesian network is an example of a very general property of a locally structured systems.

8. To which does the local structure is associated?

a) Hybrid

b) Dependent

c) Linear

d) None of the mentioned

View Answer

Explanation: Local structure is usually associated with linear rather than exponential growth in complexity.

a) Partially connected

b) Fully connected

c) Local connected

d) None of the mentioned

View Answer

Explanation: None.

10. What is the consequence between a node and its predecessors while creating Bayesian network?

a) Conditionally dependent

b) Dependent

c) Conditionally independent

d) Both a & b

View Answer

Explanation: The semantics to derive a method for constructing Bayesian networks were led to the consequence that a node can be conditionally independent of its predecessors.

**Sanfoundry Global Education & Learning Series – Artificial Intelligence. **

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