plot,dbs-method {pdfCluster} | R Documentation |
Plot objects of class dbs
Description
This function provides a graphical tool to display diagnostics of density-based cluster analysis by means of the density-based silhouette information.
Usage
## S4 method for signature 'dbs'
plot(x, y , xlab = "", ylab = "", col = NULL, lwd = 3, cex = 0.9,
cex.axis = 0.5, main = NULL, labels = FALSE, ...)
Arguments
x |
An object of |
y |
Not used; for compatibility with generic plot; |
xlab |
A title for the x axis; |
ylab |
A title for the y axis; |
col |
A specification for the plotting color. Default are colors in palette corresponding to the group labels; |
lwd |
A specification for the width of the bars in the plot; |
cex |
A numerical value giving the amount by which plotting text and symbols should be magnified relative to the default; |
cex.axis |
The magnification to be used for axis annotation relative to the current setting of cex; |
main |
An overall title for the plot; |
labels |
Logical. Should row index of data be added to the plot? |
... |
Further arguments to be passed to |
Details
After computing the density-based silhouette index by applying dbs-methods
, data are partitioned
into the clusters, sorted in a decreasing order with respect to their dbs value and displayed
on a bar graph.
Methods
signature(x = "dbs", y = "missing")
-
S4 method for plotting objects of
dbs-class
See Also
Examples
#example 1: no groups in data
#random generation of group labels
set.seed(54321)
x <- rnorm(50)
groups <- sample(1:2, 50, replace=TRUE)
groups
dsil <- dbs(x=as.matrix(x), clusters=groups)
dsil
summary(dsil)
plot(dsil, labels=TRUE, lwd=6)
#example 2: wines data
# load data
data(wine)
gr <- wine[,1]
# select a subset of variables
x <- wine[, c(2,5,8)]
#clustering
cl <- pdfCluster(x)
dsil <- dbs(cl)
plot(dsil)