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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the main difference between GMMs and K-Means clustering?
💡 Hint: Think about how clusters are formed in each method.
Question 2
Easy
Define what a Gaussian distribution is.
💡 Hint: Recall the bell curve shape.
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 is one key advantage of using GMMs over K-Means clustering?
- They are always faster to compute.
- They handle elliptical clusters better.
- They require labeled data.
💡 Hint: Think about cluster shapes that GMMs can model.
Question 2
True or False: GMMs provide hard assignments of data points to clusters.
- True
- False
💡 Hint: Recall how GMMs treat data points regarding cluster membership.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Suppose you conduct a clustering analysis and observe that GMMs report more stable results than K-Means in partitioning customer data. Discuss the potential reasons for this stability.
💡 Hint: Consider the implications of soft versus hard assignments.
Question 2
Build a small example dataset with 2D points representing two clusters of different shapes. Explain how GMM would approach clustering these points compared to K-Means.
💡 Hint: Visualize the clusters and think about what shape they take.
Challenge and get performance evaluation