Practice Markov Random Fields (MRFs) / Undirected Graphical Models - 4.2.2 | 4. Graphical Models & Probabilistic Inference | Advance Machine Learning
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What type of graph do Markov Random Fields use?

πŸ’‘ Hint: Remember, it's the opposite of directed graphs.

Question 2

Easy

What is a clique?

πŸ’‘ Hint: Think of it as a group where everyone knows each other.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What type of graphical model is a Markov Random Field?

  • Directed
  • Undirected
  • Cyclic

πŸ’‘ Hint: Think about the directionality of edges in the graph.

Question 2

True or False: In MRFs, the relationship between variables is represented by directed edges.

  • True
  • False

πŸ’‘ Hint: Recall the definition of MRFs.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Consider an MRF that consists of four variables X1, X2, X3, and X4. If the potential functions are Ο†(X1, X2), Ο†(X2, X3), and Ο†(X3, X4), derive the joint probability expression.

πŸ’‘ Hint: Think of how each potential function contributes to the overall structure.

Question 2

Discuss why MRFs could be inappropriate for certain types of problems that require unidirectional dependencies. Provide an example.

πŸ’‘ Hint: Consider how temporal sequences impact relationships and if direction is vital.

Challenge and get performance evaluation