\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.