Question: What does the silhouette score measure in clustering?
Options:
The accuracy of predictions
The compactness and separation of clusters
The number of clusters
The speed of the algorithm
Correct Answer: The compactness and separation of clusters
Solution:
The silhouette score evaluates how similar an object is to its own cluster compared to other clusters.
What does the silhouette score measure in clustering?
Practice Questions
Q1
What does the silhouette score measure in clustering?
The accuracy of predictions
The compactness and separation of clusters
The number of clusters
The speed of the algorithm
Questions & Step-by-Step Solutions
What does the silhouette score measure in clustering?
Step 1: Understand that clustering is a way to group similar items together.
Step 2: Each item in a cluster should be more similar to other items in the same cluster than to items in different clusters.
Step 3: The silhouette score is a number that helps us measure this similarity.
Step 4: A high silhouette score means that an item is well matched to its own cluster and poorly matched to neighboring clusters.
Step 5: A low silhouette score means that an item may be in the wrong cluster or is not well separated from other clusters.
Silhouette Score – The silhouette score measures the quality of clustering by comparing the distance between a data point and its own cluster to the distance between that data point and the nearest cluster.
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