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.