Practice - Limitations of Mixture Models
Practice Questions
Test your understanding with targeted questions
What is non-identifiability in the context of mixture models?
💡 Hint: Think about how different formulas can yield the same result.
What must we ensure when using the EM algorithm?
💡 Hint: Remember the metaphor of climbing a hill?
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is a key limitation of mixture models related to parameters?
💡 Hint: Think about what complicates the interpretation of results.
True or False: Local maxima can result in incorrect clustering solutions.
💡 Hint: Consider how climbing a hill works.
2 more questions available
Challenge Problems
Push your limits with advanced challenges
Design an experiment to test the impact of varying K on cluster quality in a dataset with known distributions. Explain your methodology.
💡 Hint: Consider how to measure 'closeness' among clusters.
Analyze a real-world dataset (e.g., customer data) where specifying K was challenging. What approach did you take?
💡 Hint: Think about tools you could use to assess the quality of different clusters.
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Reference links
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