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Welcome to the Uncertain Knowledge MCQs Page

Dive deep into the fascinating world of Uncertain Knowledge with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Uncertain Knowledge, a crucial aspect of Artificial Intelligence. In this section, you will encounter a diverse range of MCQs that cover various aspects of Uncertain Knowledge, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Artificial Intelligence.

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Check out the MCQs below to embark on an enriching journey through Uncertain Knowledge. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Artificial Intelligence.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Uncertain Knowledge. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Uncertain Knowledge MCQs | Page 5 of 6

Explore more Topics under Artificial Intelligence

Discuss
Answer: (d).All of the above
Q42.
Bayesian Belief Network is also known as ?
Discuss
Answer: (d).All of the above
Q43.
Bayesian Network consist of ?
Discuss
Answer: (a).2 components
Q44.
The generalized form of Bayesian network that represents and solve decision problems under uncertain knowledge is known as an?
Discuss
Answer: (c).Influence diagram
Q45.
How many component does Bayesian network have?

a.

2

b.

3

c.

4

d.

5

Discuss
Answer: (a).2
Q46.
The Bayesian network graph does not contain any cyclic graph. Hence, it is known as a
Discuss
Answer: (b).DAG
Q47.
In a Bayesian network variable is?
Discuss
Answer: (c).both a and b
Q48.
If we have variables x1, x2, x3,....., xn, then the probabilities of a different combination of x1, x2, x3.. xn, are known as?
Discuss
Answer: (d).Joint probability distribution
Q49.
The nodes and links form the structure of the Bayesian network, and we call this the ?
Discuss
Answer: (a).structural specification
Q50.
Which of the following are used for modeling times series and sequences?
Discuss
Answer: (b).Dynamic Bayesian networks
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