Recall & Review
beginner
What is the purpose of choosing the right K in clustering?
Choosing the right K helps find the best number of groups (clusters) in data so that each group is meaningful and different from others.
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beginner
What does the elbow method show in a graph?
The elbow method plots the total distance of points to their cluster centers for different K values. The 'elbow' point where the decrease slows down suggests a good K.
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intermediate
How is the silhouette score used to choose K?
The silhouette score measures how well each point fits in its cluster compared to others. Higher average scores mean better clustering, helping pick the best K.
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intermediate
What does a low silhouette score indicate about clusters?
A low silhouette score means clusters overlap or points are not well matched to their cluster, suggesting a poor choice of K or clustering.
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advanced
Why might the elbow method sometimes be unclear?
Sometimes the graph does not have a clear 'elbow' point, making it hard to decide K. In such cases, other methods like silhouette score help.
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What does the 'elbow' in the elbow method graph represent?
Which score indicates better clustering quality?
If silhouette scores are low for all K values, what does it suggest?
What is a common use of the elbow method?
Which method can help when the elbow method is unclear?
Explain how the elbow method helps in choosing the number of clusters K.
Describe what the silhouette score measures and how it guides choosing K.