Database Reference
In-Depth Information
Hierarchical clustering
Hierarchical clustering is a structured clustering approach that results in a multilevel hier-
archy of clusters, where each cluster might contain many subclusters (or child clusters).
Each child cluster is, thus, linked to the parent cluster. This form of clustering is often also
called tree clustering.
Agglomerative clustering is a bottom-up approach where:
• Each data point begins in its own cluster
• The similarity (or distance) between each pair of clusters is evaluated
• The pair of clusters that are most similar are found; this pair is then merged to form
a new cluster
• The process is repeated until only one top-level cluster remains
Divisive clustering is a top-down approach that works in reverse, starting with one cluster
and at each stage, splitting a cluster into two, until all data points are allocated to their own
bottom-level cluster.
Note
You can find more information at http://en.wikipedia.org/wiki/Hierarchical_clustering .
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