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In evaluating clustering algorithms, which metric assesses the compactness of cl
In evaluating clustering algorithms, which metric assesses the compactness of clusters?
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Practice Questions
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Q1
In evaluating clustering algorithms, which metric assesses the compactness of clusters?
Silhouette Score
Accuracy
F1 Score
Mean Squared Error
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Silhouette Score measures how similar an object is to its own cluster compared to other clusters.
Questions & Step-by-step Solutions
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Q
Q: In evaluating clustering algorithms, which metric assesses the compactness of clusters?
Solution:
Silhouette Score measures how similar an object is to its own cluster compared to other clusters.
Steps: 5
Show Steps
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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