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What metric is commonly used to evaluate the performance of clustering algorithm

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Question: What metric is commonly used to evaluate the performance of clustering algorithms?

Options:

  1. Accuracy
  2. Silhouette score
  3. F1 score
  4. Mean squared error

Correct Answer: Silhouette score

Solution: 

The silhouette score measures how similar an object is to its own cluster compared to other clusters, providing insight into clustering quality.

What metric is commonly used to evaluate the performance of clustering algorithm

Practice Questions

Q1
What metric is commonly used to evaluate the performance of clustering algorithms?
  1. Accuracy
  2. Silhouette score
  3. F1 score
  4. Mean squared error

Questions & Step-by-Step Solutions

What metric is commonly used to evaluate the performance of clustering algorithms?
  • Step 1: Understand what clustering algorithms do. They group similar data points together.
  • Step 2: Learn that we need a way to measure how good these groups (clusters) are.
  • Step 3: Discover the silhouette score, which is a common metric for this purpose.
  • Step 4: Know that the silhouette score compares how close a data point is to its own cluster versus other clusters.
  • Step 5: Realize that a higher silhouette score means better clustering quality.
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