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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is clustering?
💡 Hint: Think about organizing items by shared characteristics.
Question 2
Easy
Name one advantage of K-Means clustering.
💡 Hint: What do we want a clustering method to be?
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 the main goal of clustering?
- Decrease dimensions
- Group similar points
- Randomly sort data
💡 Hint: What is the purpose of clustering in machine learning?
Question 2
True or False: DBSCAN requires you to predefine the number of clusters.
- True
- False
💡 Hint: Think about how DBSCAN groups data points.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Suppose you apply K-Means clustering on a dataset and received poor results due to sensitivity to outliers. What approaches can you take to mitigate this issue?
💡 Hint: Think about how data transformations can affect clustering.
Question 2
A manager wants to use DBSCAN but is unsure of how to set its parameters. What general advice would you give to help them choose optimal values for eps and minPts?
💡 Hint: Consider the density of clusters when adjusting these parameters.
Challenge and get performance evaluation