Partitioning Around Medoids (PAM) Object
The objects of class "pam" represent a partitioning of a
dataset into clusters.
A legitimate pam object is a list with the following components:
medoids |
the medoids or representative objects of the
clusters. If a dissimilarity matrix was given as input to
|
id.med |
integer vector of indices giving the medoid observation numbers. |
clustering |
the clustering vector, see |
objective |
the objective function after the first and second
step of the |
isolation |
vector with length equal to the number of clusters, specifying which
clusters are isolated clusters (L- or L*-clusters) and which clusters are
not isolated. |
clusinfo |
matrix, 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). |
silinfo |
list with silhouette width information, see
|
diss |
dissimilarity (maybe NULL), see |
call |
generating call, see |
data |
(possibibly standardized) see |
These objects are returned from pam.
The "pam" class has methods for the following generic functions:
print, summary.
The class "pam" inherits from "partition".
Therefore, the generic functions plot and clusplot can
be used on a pam object.
## Use the silhouette widths for assessing the best number of clusters,
## following a one-dimensional example from Christian Hennig :
##
x <- c(rnorm(50), rnorm(50,mean=5), rnorm(30,mean=15))
asw <- numeric(20)
## Note that "k=1" won't work!
for (k in 2:20)
asw[k] <- pam(x, k) $ silinfo $ avg.width
k.best <- which.max(asw)
cat("silhouette-optimal number of clusters:", k.best, "\n")
plot(1:20, asw, type= "h", main = "pam() clustering assessment",
xlab= "k (# clusters)", ylab = "average silhouette width")
axis(1, k.best, paste("best",k.best,sep="\n"), col = "red", col.axis = "red")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.