1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
|
\name{plot.partition}
\alias{plot.partition}
\title{Plot of a Partition of the Data Set}
\description{Creates plots for visualizing a \code{partition} object.}
\usage{
\method{plot}{partition}(x, ask = FALSE, which.plots = NULL,
nmax.lab = 40, max.strlen = 5, data = x$data, dist = NULL,
stand = FALSE, lines = 2,
shade = FALSE, color = FALSE, labels = 0, plotchar = TRUE,
span = TRUE, xlim = NULL, ylim = NULL, main = NULL, \dots)
}
\arguments{
\item{x}{an object of class \code{"partition"}, typically created by the
functions \code{\link{pam}}, \code{\link{clara}}, or \code{\link{fanny}}.}
\item{ask}{logical; if true and \code{which.plots} is \code{NULL},
\code{plot.partition} operates in interactive mode, via \code{\link{menu}}.}
\item{which.plots}{integer vector or NULL (default), the latter
producing both plots. Otherwise, \code{which.plots} must contain
integers of \code{1} for a \emph{clusplot} or \code{2} for
\emph{silhouette}.}
\item{nmax.lab}{integer indicating the number of labels which is
considered too large for single-name labeling the silhouette plot.}
\item{max.strlen}{positive integer giving the length to which
strings are truncated in silhouette plot labeling.}
\item{data}{numeric matrix with the scaled data; per default taken
from the partition object \code{x}, but can be specified explicitly.}
\item{dist}{when \code{x} does not have a \code{diss} component as for
\code{\link{pam}(*, keep.diss=FALSE)}, \code{dist} must be the
dissimilarity if a clusplot is desired.}
\item{stand,lines,shade,color,labels,plotchar,span,xlim,ylim,main, \dots}{
All optional arguments available for the \code{\link{clusplot.default}}
function (except for the \code{diss} one) and graphical parameters
(see \code{\link{par}}) may also be supplied as arguments to this function.}
}
\section{Side Effects}{
An appropriate plot is produced on the current graphics device. This
can be one or both of the following choices:
\cr Clusplot
\cr Silhouette plot
}
\details{
When \code{ask= TRUE}, rather than producing each plot sequentially,
\code{plot.partition} displays a menu listing all the plots that can
be produced.
If the menu is not desired but a pause between plots is still wanted,
call \code{par(ask= TRUE)} before invoking the plot command.
The \emph{clusplot} of a cluster partition consists of a two-dimensional
representation of the observations, in which the clusters are
indicated by ellipses (see \code{\link{clusplot.partition}} for more
details).
The \emph{silhouette plot} of a nonhierarchical clustering is fully
described in Rousseeuw (1987) and in chapter 2 of Kaufman and
Rousseeuw (1990).
For each observation i, a bar is drawn, representing its silhouette
width s(i), see \code{\link{silhouette}} for details.
Observations are grouped per cluster, starting with cluster 1 at the
top. Observations with a large s(i) (almost 1) are very well
clustered, a small s(i) (around 0) means that the observation lies
between two clusters, and observations with a negative s(i) are
probably placed in the wrong cluster.
A clustering can be performed for several values of \code{k} (the number of
clusters). Finally, choose the value of \code{k} with the largest overall
average silhouette width.
}
\note{
In the silhouette plot, observation labels are only printed when the
number of observations is less than \code{nmax.lab} (40, by default),
for readability. Moreover, observation labels are truncated to
maximally \code{max.strlen} (5) characters. \cr
For more flexibility, use \code{plot(silhouette(x), ...)}, see
\code{\link{plot.silhouette}}.
}
\references{
Rousseeuw, P.J. (1987)
Silhouettes: A graphical aid to the interpretation and validation of
cluster analysis. \emph{J. Comput. Appl. Math.}, \bold{20}, 53--65.
Further, the references in \code{\link{plot.agnes}}.
}
\seealso{
\code{\link{partition.object}}, \code{\link{clusplot.partition}},
\code{\link{clusplot.default}}, \code{\link{pam}},
\code{\link{pam.object}}, \code{\link{clara}},
\code{\link{clara.object}}, \code{\link{fanny}},
\code{\link{fanny.object}}, \code{\link{par}}.
}
\examples{
## generate 25 objects, divided into 2 clusters.
x <- rbind(cbind(rnorm(10,0,0.5), rnorm(10,0,0.5)),
cbind(rnorm(15,5,0.5), rnorm(15,5,0.5)))
plot(pam(x, 2))
## Save space not keeping data in clus.object, and still clusplot() it:
data(xclara)
cx <- clara(xclara, 3, keep.data = FALSE)
cx$data # is NULL
plot(cx, data = xclara)
}
\keyword{cluster}
\keyword{hplot}
% Converted by Sd2Rd version 0.3-2.
|
