partition.object: Partitioning Object

Description

The objects of class "partition" represent a partitioning of a dataset into clusters.

a "partition" object is a list with the following (and typically more) components:
clusteringthe 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.
callthe matched call generating the object.
silinfoa 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 silhouette [object Object],[object Object],[object Object] This information is also needed to construct a silhouette plot of the clustering, see plot.partition.
Note that avg.width can be maximized over different clusterings (e.g. with varying number of clusters) to choose an optimal clustering.
objectivevalue of criterion maximized during the partitioning algorithm, may more than one entry for different stages.
dissan object of class "dissimilarity", representing the total dissimilarity matrix of the dataset (or relevant subset, e.g. for clara).
dataa 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.

These objects are returned from pam, clara or fanny.

The "partition" class has a method for the following generic functions: plot, clusplot.

The following classes inherit from class "partition" : "pam", "clara" and "fanny".