In evaluating clustering algorithms, which metric assesses the compactness of cl

In evaluating clustering algorithms, which metric assesses the compactness of clusters?

In evaluating clustering algorithms, which metric assesses the compactness of clusters?

Step 1: Understand what clustering algorithms do. They group similar data points together.
Step 2: Know that we want to evaluate how well these groups (clusters) are formed.
Step 3: Learn about the Silhouette Score, which is a metric used for this evaluation.
Step 4: The Silhouette Score measures how close a data point is to points in its own cluster versus points in other clusters.
Step 5: A high Silhouette Score means the data point is well matched to its own cluster and poorly matched to neighboring clusters.

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