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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the primary purpose of Gaussian Mixture Models?
💡 Hint: Think about how GMMs differ in assigning data points to clusters.
Question 2
Easy
What is the key function of PCA?
💡 Hint: Consider what happens to data with many features when using PCA.
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 a key advantage of GMMs compared to K-Means?
- GMMs always use spherical clusters.
- GMMs assign probabilities to data points instead of strict cluster memberships.
- GMMs require labeled data.
💡 Hint: Think about how uniquely each method categorizes data points.
Question 2
True or False: PCA is used primarily for data visualization rather than noise reduction.
- True
- False
💡 Hint: Recall the dual objectives of PCA.
Solve 3 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You have a dataset with features that are highly correlated. Describe why feature extraction might be a better approach than feature selection in this scenario.
💡 Hint: Think about the impact of correlation among features on interpretation.
Question 2
Given a high-dimensional dataset with clear, non-spherical clusters, would you select GMM or K-Means? Justify your choice.
💡 Hint: Consider the nature of the cluster shapes in your decision.
Challenge and get performance evaluation