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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does DBSCAN stand for?
💡 Hint: Think about what each part of the acronym represents.
Question 2
Easy
What are the two main parameters of DBSCAN?
💡 Hint: What does each parameter measure or define?
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 DBSCAN primarily focus on for clustering?
- Distance
- Density
- Number of clusters
💡 Hint: Consider how points are grouped together.
Question 2
True or False: DBSCAN can only form spherical clusters.
- True
- False
💡 Hint: Think about the capabilities of density-based clustering.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
In a dataset with five clusters of different densities, design a DBSCAN algorithm implementation. Describe how you would tune the parameters.
💡 Hint: Think about how density impacts clustering and potential adjustments.
Question 2
Analyze the consequences of using a fixed ε value on a dataset with varying cluster densities. What issues could arise?
💡 Hint: Consider how changing densities influence the clustering outcome.
Challenge and get performance evaluation