Glossary term
Glossary term
Foundations
A category of clustering algorithms that create a tree of clusters. Hierarchical clustering is well-suited to hierarchical data, such as botanical taxonomies. There are two types of hierarchical clustering algorithms:
Agglomerative clustering first assigns every example to its own cluster, and iteratively merges the closest clusters to create a hierarchical tree.
Divisive clustering first groups all examples into one cluster and then iteratively divides the cluster into a hierarchical tree.
Contrast with centroid-based clustering.
See Clustering algorithms in the Clustering course for more information.
Created for this library
A retail analytics team uses hierarchical clustering on customer purchase histories to inspect the dendrogram before choosing a final number of segments.
A genomics team uses hierarchical clustering on gene expression profiles to discover groups of co-regulated genes for biologists to interpret.
A research team uses hierarchical clustering on news articles to expose a coarse-to-fine topic structure for editors.
Definition source: Google for Developers Machine Learning Glossary | Creative Commons Attribution 4.0 License