Hierarchical Cluster Analysis
A method of cluster analysis that builds a hierarchy from the individual elements by progressively merging clusters.
Implications
A method of cluster analysis that builds a hierarchy of clusters by either merging smaller clusters into larger ones (agglomerative) or dividing larger clusters into smaller ones (divisive), often used in market segmentation, biology, and image analysis.
Example
Example: A data scientist uses hierarchical cluster analysis to group customers based on purchasing behavior, creating a dendrogram that visually represents the relationships between different customer segments.
Related Terms
Different from k-means clustering, which requires the number of clusters to be specified in advance, hierarchical clustering builds a tree-like structure that can be cut at different levels to reveal different numbers of clusters.
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