SciPy - Clustering and Distance
Which metric measures how similar an object is to its own cluster compared to other clusters?
Which metric measures how similar an object is to its own cluster compared to other clusters?
easy📝 Conceptual Q1 of 15
Step-by-Step Solution
Solution:
Step 1: Understand the Silhouette Score concept
The Silhouette Score calculates how close each point in one cluster is to points in the neighboring clusters.Step 2: Compare with other metrics
Davies-Bouldin and Calinski-Harabasz measure cluster separation and compactness, while Adjusted Rand Index compares cluster labels to true labels.Final Answer:
Silhouette Score -> Option CQuick Check:
Silhouette Score = B [OK]
Quick Trick: Silhouette compares intra- and inter-cluster distances [OK]
Common Mistakes:
- Confusing Adjusted Rand Index as it needs true labels
- Mixing Davies-Bouldin with Silhouette Score
- Thinking Calinski-Harabasz measures similarity per point
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