plot,dbs-method | R Documentation |
This function provides a graphical tool to display diagnostics of density-based cluster analysis by means of the density-based silhouette information.
## 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, ...)
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 |
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.
signature(x = "dbs", y = "missing")
S4 method for plotting objects of dbs-class
dbs
, dbs-class
, silhouette
.
#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)
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