In hierarchical clustering, what is the difference between agglomerative and divisive methods?
Correct Answer: Agglomerative clustering merges points into clusters, while divisive clustering splits clusters into smaller ones.
- Step 1: Understand that hierarchical clustering is a method of grouping data points into clusters based on their similarities.
- Step 2: Learn about agglomerative clustering, which starts with each data point as its own cluster.
- Step 3: In agglomerative clustering, the algorithm merges the closest clusters together step by step until all points are in one cluster.
- Step 4: Now, learn about divisive clustering, which is the opposite approach.
- Step 5: In divisive clustering, you start with all data points in one big cluster.
- Step 6: The algorithm then splits this big cluster into smaller clusters step by step until each point is its own cluster.
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