Guide-linked quiz · Medium Level

Silhouette Score and Cluster Evaluation Quiz

Calculate per-point silhouette values and distinguish internal geometric diagnostics from cluster utility and alternative indices.

Question 1 of 8

With a=2 and b=5, what is the silhouette coefficient (b-a)/max(a,b)?

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  1. With a=2 and b=5, what is the silhouette coefficient (b-a)/max(a,b)?
    • 0.6
    • -0.6
    • 0.4
    • 1.5
  2. A point has a=4 and b=3. What does its negative silhouette indicate?
    • Its assigned cluster has zero observations
    • It is, on average, closer to another cluster under the chosen distance
    • The global score must be negative
    • The feature scaling is proven correct
  3. What does a silhouette near zero commonly suggest for one observation?
    • Its class label is known
    • It is perfectly separated from all clusters
    • It lies near a boundary between its own and another cluster
    • The clustering has one cluster only
  4. Which direction is generally preferred for the Davies-Bouldin index?
    • A value matching the silhouette range
    • Higher values
    • Exactly zero for every useful partition
    • Lower values
  5. Why should raw Davies-Bouldin and Calinski-Harabasz values not be compared directly?
    • Both are probability estimates between zero and one
    • They use different formulas, scales and preferred directions
    • They require identical units by definition
    • One is always the reciprocal of the other
  6. Why can an average silhouette hide a cluster-specific problem?
    • Every sample receives a different formula
    • Silhouette uses only labels and no distances
    • A sample-weighted mean can mask weak values in a smaller group
    • A negative value is omitted automatically
  7. What does a high silhouette score fail to establish by itself?
    • That labels were assigned
    • That within and between distances were calculated
    • That the chosen metric was used
    • That the clusters are useful for the downstream task
  8. When is the silhouette score undefined in common implementations?
    • For degenerate labelings with one cluster or one cluster per sample
    • Whenever the average coefficient is positive
    • When a cluster has two observations
    • When distances use standardized features

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