This is documentation for Mathematica 6, which was
based on an earlier version of the Wolfram Language.
 Hierarchical Clustering Package Symbol

# Agglomerate

 Agglomerate[{e1, e2, ...}]gives an hierarchical clustering of the elements e1, e2, .... Agglomerate[{e1->v1, e2->v2, ...}] represents ei with vi in each cluster. Agglomerate[{e1, e2, ...}->{v1, v2, ...}] represents ei with vi in each cluster.
• Agglomerate gives a Cluster object.
• The data elements ei can be numeric lists, matrices, or tensors, lists of Boolean elements, or strings with each ei having the same dimensions.
• The following options can be given:
 DistanceFunction Automatic the distance or dissimilarity measure to use Linkage Automatic the clustering linkage algorithm to use
• The setting for DistanceFunction can be any distance or dissimilarity function or a pure function f defining a distance between two values.
• Linkage defines the intercluster dissimilarity, given the dissimilarities between member elements.
• Possible settings for the Linkage option include:
 "Single" smallest intercluster dissimilarity "Average" average intercluster dissimilarity "Complete" largest intercluster dissimilarity "Weighted" weighted average intercluster dissimilarity "Centroid" distance from cluster centroids "Median" distance from cluster medians "Ward" Ward's minimum variance dissimilarity f a pure function
• The function f defines a distance from a cluster k to the new cluster formed by fusing clusters i and j.
• The arguments supplied to f are dik, djk, dij, ni, nj, and nk, where d is the distance between clusters and n is the number of elements in a cluster.
Needs["HierarchicalClustering`"]
Obtain a cluster hierarchy from a list of numbers:
 Out[2]=
 Options   (2)