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constructs a cluster hierarchy based on the distance or dissimilarity matrix m.

associates the elements of list with the rows of the matrix m in the cluster hierarchy.
  • DirectAgglomerate[m] labels each element by its row position in the matrix m.
  • The distance matrix m can be any symmetric matrix.
  • The method used to determine intercluster dissimilarity can be specified using the Linkage option.
  • Possible settings for the Linkage option include:
"Single"smallest intercluster dissimilarity
"Average"average intercluster dissimilarity
"Complete"largest intercluster dissimilarity
"WeightedAverage"weighted average intercluster dissimilarity
"Centroid"distance from cluster centroids
"Median"distance from cluster medians
"Ward"Ward's minimum variance dissimilarity
fa 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 , , , , , and , where d is the distance between clusters and n is the number of elements in a cluster.
Obtain a cluster hierarchy from a distance matrix:
Use labels to represent the rows:
Obtain a cluster hierarchy from a distance matrix:
Click for copyable input
Use labels to represent the rows:
Click for copyable input
Cluster hierarchy using Ward's linkage: