Chapter 4. Agglomerative Clustering Using hclust()

Unlike partition clustering, which requires the user to specify the number of k clusters and create homogeneous k groups, hierarchical clustering defines clusters without user intervention from distances in the data and defines a tree of clusters from this. Hierarchical clustering is particularly useful when the data is suspected to be hierarchical (leaves nested in nodes nested in higher level nodes). It can also be used to determine the number of clusters to be used in k-means clustering. Hierarchical clustering can be agglomerative or divisive. Agglomerative clustering usually yields a higher number of clusters, with less leaf nodes by cluster.

Agglomerative clustering refers to the use of algorithms, ...

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