Definition:
Cluster separation measures how far apart different clusters are from one another. It is a proxy for cluster distinctiveness.
Common Approaches:
- Inter-cluster distance
- Davies–Bouldin index
- Silhouette score, Silhouette Analysis (combines cohesion and separation)
Exploratory Questions:
- What does high separation mean if internal density is low?
- How does Curse of dimensionality affect separation metrics?
- What clustering algorithms maximize separation explicitly?