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In hierarchical clustering, what does agglomerative clustering do?

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Question: In hierarchical clustering, what does agglomerative clustering do?

Options:

  1. Starts with all data points as individual clusters and merges them
  2. Starts with one cluster and splits it into smaller clusters
  3. Randomly assigns data points to clusters
  4. Uses a predefined number of clusters

Correct Answer: Starts with all data points as individual clusters and merges them

Solution: 

Agglomerative clustering begins with each data point as its own cluster and progressively merges them based on their similarities.

In hierarchical clustering, what does agglomerative clustering do?

Practice Questions

Q1
In hierarchical clustering, what does agglomerative clustering do?
  1. Starts with all data points as individual clusters and merges them
  2. Starts with one cluster and splits it into smaller clusters
  3. Randomly assigns data points to clusters
  4. Uses a predefined number of clusters

Questions & Step-by-Step Solutions

In hierarchical clustering, what does agglomerative clustering do?
Correct Answer: Agglomerative clustering merges clusters based on similarities.
  • Step 1: Start with each data point as its own separate cluster.
  • Step 2: Calculate the similarity between each pair of clusters.
  • Step 3: Find the two clusters that are the most similar to each other.
  • Step 4: Merge these two similar clusters into one larger cluster.
  • Step 5: Repeat steps 2 to 4 until all data points are merged into a single cluster or until a desired number of clusters is reached.
  • Agglomerative Clustering – Agglomerative clustering is a bottom-up approach in hierarchical clustering where each data point starts as its own cluster and clusters are merged based on similarity.
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