In hierarchical clustering, what is agglomerative clustering?
Practice Questions
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Q1
In hierarchical clustering, what is agglomerative clustering?
A bottom-up approach to cluster formation
A top-down approach to cluster formation
A method that requires prior knowledge of clusters
A technique that uses K-means as a base
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.
Questions & Step-by-step Solutions
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Q
Q: In hierarchical clustering, what is agglomerative clustering?
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.
Steps: 5
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.
