The objects of class
"partition" represent a partitioning of a dataset into clusters.
"partition" object is a list with the following (and typically more) components:
- the clustering vector. An integer vector of length n, the number of observations, giving for each observation the number (`id') of the cluster to which it belongs.
- the matched
callgenerating the object.
- a list with all silhouette information, only available when the number of clusters is non-trivial, i.e., 1 < k < n and then has the following components, see
- an (n x 3) matrix, as returned by
silhouette(), with for each observation i the cluster to which i belongs, as well as the neighbor cluster of i (the cluster, not containing i, for which the average dissimilarity between its observations and i is minimal), and the silhouette width s(i) of the observation.
- the average silhouette width per cluster.
- the average silhouette width for the dataset, i.e., simply the average of s(i) over all observations i.
This information is also needed to construct a silhouette plot of the clustering, see
avg.widthcan be maximized over different clusterings (e.g. with varying number of clusters) to choose an optimal clustering.
- value of criterion maximized during the partitioning algorithm, may more than one entry for different stages.
- an object of class
"dissimilarity", representing the total dissimilarity matrix of the dataset (or relevant subset, e.g. for
- a matrix containing the original or standardized data. This might be missing to save memory or when a dissimilarity matrix was given as input structure to the clustering method.
The following classes inherit from class
Documentation reproduced from package cluster, version 1.14.4. License: GPL (>= 2)