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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does K in K-Means represent?
💡 Hint: It signifies the count of clusters.
Question 2
Easy
What does a dendrogram represent?
💡 Hint: Think of it as a tree diagram.
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 idea behind K-Means clustering?
- It creates one cluster for all points
- It partitions data into K clusters
- It requires no initial configuration
💡 Hint: Remember what K represents in K-Means.
Question 2
Is DBSCAN sensitive to outliers?
- True
- False
💡 Hint: Recall how DBSCAN treats points that don’t belong to any cluster.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Analyze a customer dataset using both K-Means and DBSCAN. Discuss how the results differ, particularly in terms of outlier detection and cluster shapes.
💡 Hint: Compare how each algorithm treats noise and cluster configuration.
Question 2
Design a study that utilizes hierarchical clustering to analyze a dataset of your choice. Outline your steps and expected outcomes.
💡 Hint: Consider what data structure you want to reveal through clustering.
Challenge and get performance evaluation