Define clusters from an agglomerative hierarchical cluster tree.
Given a hierarchical cluster tree Z generated by the linkage
function, cluster defines clusters, using a threshold value C to
identify new clusters (’Cutoff’) or according to a maximum number of desired
clusters N (’MaxClust’).
criterion is used to choose the criterion for defining clusters, which
can be either "inconsistent" (default) or "distance". When using
"inconsistent", cluster compares the threshold value C to the
inconsistency coefficient of each link; when using "distance", cluster
compares the threshold value C to the height of each link.
D is the depth used to evaluate the inconsistency coefficient, its
default value is 2.
cluster uses "distance" as a criterion for defining new clusters when
it is used the ’MaxClust’ method.
See also: clusterdata,dendrogram,inconsistent,kmeans,linkage,pdist.
Package: statistics