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== Cluster Linkage ==
In order to decide which clusters should be combined (for agglomerative), or where a cluster should be split (for divisive), a measure of dissimilarity between sets of observations is required. In most methods of hierarchical clustering, this is achieved by use of an appropriate [[distance]] ''d'', such as the Euclidean distance, between ''single'' observations of the data set, and a linkage criterion, which specifies the dissimilarity of ''sets'' as a function of the pairwise distances of observations in the sets. The choice of metric as well as linkage can have a major impact on the result of the clustering, where the lower level metric determines which objects are most [[similarity measure|similar]], whereas the linkage criterion influences the shape of the clusters. For example, complete-linkage tends to produce more spherical clusters than single-linkage.
The linkage criterion determines the distance between sets of observations as a function of the pairwise distances between observations.
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