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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What are the two main steps of the EM algorithm?
💡 Hint: Think about the actions performed in each step.
Question 2
Easy
Define a latent variable.
💡 Hint: Consider what is hidden or not visible.
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 does the E-step of the EM algorithm involve?
- Maximizing log-likelihood
- Estimating posterior probabilities
- Updating model parameters
💡 Hint: Think about what the algorithm does in the first part.
Question 2
True or False: The EM algorithm guarantees finding the global maximum in optimization.
- True
- False
💡 Hint: Consider the nature of optimization.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Using the EM algorithm, suppose you need to analyze a dataset with missing values. Discuss how the E and M steps would be applied in your analysis.
💡 Hint: Think about how missing data influences the estimation process.
Question 2
Design a brief experiment to test different initialization parameters in the EM algorithm applied to a GMM. What outcomes would you expect and how would you analyze them?
💡 Hint: Experiment with different starting points for optimization.
Challenge and get performance evaluation