Which evaluation metric is best for assessing clustering algorithms?

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Question: Which evaluation metric is best for assessing clustering algorithms?

Options:

Correct Answer: Silhouette Score

Solution:

Silhouette Score is used to evaluate clustering algorithms by measuring how similar an object is to its own cluster compared to other clusters.

Which evaluation metric is best for assessing clustering algorithms?

Which evaluation metric is best for assessing clustering algorithms?

Step 1: Understand what clustering is. Clustering is a way to group similar items together.
Step 2: Know that we need a way to measure how good our clusters are.
Step 3: Learn about the Silhouette Score. It helps us see how well each item fits in its cluster.
Step 4: The Silhouette Score ranges from -1 to 1. A score close to 1 means the item is well placed in its cluster.
Step 5: Compare the Silhouette Score of different clustering results to find the best one.

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