Partitioning Object
partition.object.RdThe objects of class "partition" represent a partitioning of a
dataset into clusters.
INHERITANCE
The following classes inherit from class "partition" :
"pam", "clara" and "fanny".
See pam.object, clara.object and
fanny.object for details.
Value
a "partition" object is a list with the following
(and typically more) components:
- clustering
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.
- call
the matched
callgenerating the object.- silinfo
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
silhouette- widths
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.- clus.avg.widths
the average silhouette width per cluster.
- avg.width
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
plot.partition.Note that
avg.widthcan be maximized over different clusterings (e.g. with varying number of clusters) to choose an optimal clustering.- objective
value of criterion maximized during the partitioning algorithm, may more than one entry for different stages.
- diss
an object of class
"dissimilarity", representing the total dissimilarity matrix of the dataset (or relevant subset, e.g. forclara).- data
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.