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Which clustering method is more suitable for discovering nested clusters?

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Question: Which clustering method is more suitable for discovering nested clusters?

Options:

  1. K-means clustering
  2. Hierarchical clustering
  3. DBSCAN
  4. Gaussian Mixture Models

Correct Answer: Hierarchical clustering

Solution: 

Hierarchical clustering is more suitable for discovering nested clusters, as it creates a tree structure that can reveal relationships at various levels of granularity.

Which clustering method is more suitable for discovering nested clusters?

Practice Questions

Q1
Which clustering method is more suitable for discovering nested clusters?
  1. K-means clustering
  2. Hierarchical clustering
  3. DBSCAN
  4. Gaussian Mixture Models

Questions & Step-by-Step Solutions

Which clustering method is more suitable for discovering nested clusters?
Correct Answer: Hierarchical clustering
  • Step 1: Understand what clustering means. Clustering is a way to group similar items together.
  • Step 2: Learn about nested clusters. Nested clusters are groups that can contain smaller groups within them.
  • Step 3: Know the types of clustering methods. There are different methods like hierarchical clustering and k-means clustering.
  • Step 4: Focus on hierarchical clustering. This method builds a tree-like structure called a dendrogram.
  • Step 5: See how the dendrogram works. It shows how clusters are formed at different levels, revealing smaller groups within larger ones.
  • Step 6: Conclude that hierarchical clustering is better for finding nested clusters because it shows relationships at various levels.
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