What is a primary advantage of using hierarchical clustering over K-means?

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Question: What is a primary advantage of using hierarchical clustering over K-means?

Options:

Correct Answer: It does not require the number of clusters to be specified in advance

Solution:

Hierarchical clustering does not require the number of clusters to be predetermined, allowing for more flexibility in cluster formation.

What is a primary advantage of using hierarchical clustering over K-means?

What is a primary advantage of using hierarchical clustering over K-means?

Step 1: Understand what clustering is. Clustering is a way to group similar items together.
Step 2: Learn about K-means clustering. K-means requires you to decide how many groups (clusters) you want before starting.
Step 3: Know about hierarchical clustering. Hierarchical clustering builds a tree of clusters without needing to set the number of clusters in advance.
Step 4: Recognize the advantage. Since hierarchical clustering does not need a fixed number of clusters, it allows you to explore different groupings and find the best fit.

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