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What is the main difference between agglomerative and divisive hierarchical clustering algorithms?
What is the main difference between agglomerative and divisive hierarchical clustering algorithms?
- Agglomerative algorithms divide one big cluster into smaller clusters from the top-down, while divisive algorithms merge clusters from the bottom-up.
- Agglomerative algorithms create a dendrogram, while divisive algorithms do not create any graphical representation.
- Agglomerative algorithms use Euclidean distance, while divisive algorithms use Manhattan distance.
- Agglomerative algorithms merge clusters from the bottom-up, while divisive algorithms divide one big cluster into smaller clusters from the top-down. (correct)
What does a root node represent in a dendrogram?
What does a root node represent in a dendrogram?
- The minimum distance between any two points in a cluster.
- A cluster formed after merging two or more smaller clusters. (correct)
- The individual data points in the dataset.
- The maximum distance between any two points in a cluster.
Which method uses the distance between the closest members of two clusters in agglomerative hierarchical clustering?
Which method uses the distance between the closest members of two clusters in agglomerative hierarchical clustering?
- Average linkage
- Centroid linkage
- Single linkage (correct)
- Complete linkage
What is the purpose of a dendrogram in hierarchical clustering?
What is the purpose of a dendrogram in hierarchical clustering?
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What is represented by leaf nodes in a dendrogram?
What is represented by leaf nodes in a dendrogram?
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