pam.object: Partitioning Around Medoids (PAM) Object
Description
The objects of class "pam" represent a partitioning of a
dataset into clusters.Value
- A legitimate
pam object is a list with the following components: - medoidsthe medoids or representative objects of the
clusters. If a dissimilarity matrix was given as input to
pam, then a vector of numbers or labels of observations is
given, else medoids is a matrix with in each row the
coordinates of one medoid. - clusteringthe clustering vector. A vector with length equal to the number of
observations, giving the number of the cluster to which each
observation belongs.
- objectivethe objective function after the first and second step of the
pam
algorithm. - clusinfomatrix, each row gives numerical information for one cluster. These
are the cardinality of the cluster (number of observations), the
maximal and average dissimilarity between the observations in the
cluster and the cluster's medoid, the diameter of the cluster
(maximal dissimilarity between two observations of the cluster), and
the separation of the cluster (minimal dissimilarity between an
observation of the cluster and an observation of another cluster).
- isolationvector with length equal to the number of clusters, specifying which
clusters are isolated clusters (L- or L*-clusters) and which clusters are
not isolated.
A cluster is an L*-cluster iff its diameter is smaller than its
separation. A cluster is an L-cluster iff for each observation i
the maximal dissimilarity between i and any other observation of the
cluster is smaller than the minimal dissimilarity between i and any
observation of another cluster. Clearly each L*-cluster is also an
L-cluster.
- silinfolist with all information necessary to construct a silhouette plot
of the clustering. This list is only available when 1 < k < n. The
first component is a matrix, 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
of i. The other two components give the average silhouette width
per cluster and the average silhouette width for the dataset. See
plot.partition for more information. - dissan object of class
"dissimilarity", representing the total
dissimilarity matrix of the dataset. - dataa matrix containing the original or standardized measurements, depending
on the
stand option of the function pam. If a
dissimilarity matrix was given as input structure, then this component
is not available.
GENERATION
These objects are returned from pam.METHODS
The "pam" class has methods for the following generic functions:
print, summary.INHERITANCE
The class "pam" inherits from "partition".
Therefore, the generic functions plot and clusplot can
be used on a pam object.