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In hierarchical clustering, what is agglomerative clustering?

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Question: In hierarchical clustering, what is agglomerative clustering?

Options:

  1. A bottom-up approach to cluster formation
  2. A top-down approach to cluster formation
  3. A method that requires prior knowledge of clusters
  4. A technique that uses K-means as a base

Correct Answer: A bottom-up approach to cluster formation

Solution: 

Agglomerative clustering is a bottom-up approach where each data point starts as its own cluster and pairs of clusters are merged as one moves up the hierarchy.

In hierarchical clustering, what is agglomerative clustering?

Practice Questions

Q1
In hierarchical clustering, what is agglomerative clustering?
  1. A bottom-up approach to cluster formation
  2. A top-down approach to cluster formation
  3. A method that requires prior knowledge of clusters
  4. A technique that uses K-means as a base

Questions & Step-by-Step Solutions

In hierarchical clustering, what is agglomerative clustering?
Correct Answer: Agglomerative clustering is a bottom-up approach in hierarchical clustering.
  • Step 1: Start with each data point as its own separate cluster.
  • Step 2: Look for the two closest clusters (or data points) based on a distance measure.
  • Step 3: Merge these two closest clusters into one larger cluster.
  • Step 4: Repeat steps 2 and 3 until all data points are merged into a single cluster or until a desired number of clusters is reached.
  • Step 5: The result is a hierarchy of clusters that can be visualized as a tree-like structure called a dendrogram.
  • Agglomerative Clustering – A bottom-up approach in hierarchical clustering where individual data points are merged into larger clusters.
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