pltree: Plot Clustering Tree of a Hierarchical Clustering

In cluster: "Finding Groups in Data": Cluster Analysis Extended Rousseeuw et al.

Plot Clustering Tree of a Hierarchical Clustering

Description

pltree() Draws a clustering tree (“dendrogram”) on the current graphics device. We provide the twins method draws the tree of a twins object, i.e., hierarchical clustering, typically resulting from agnes() or diana().

Usage

pltree(x, ...)
## S3 method for class 'twins'
pltree(x, main = paste("Dendrogram of ", deparse1(x$call)),
             labels = NULL, ylab = "Height", ...)

Arguments

x	in general, an R object for which a pltree method is defined; specifically, an object of class "twins", typically created by either agnes() or diana().
main	main title with a sensible default.
labels	labels to use; the default is constructed from x.
ylab	label for y-axis.
...	graphical parameters (see par) may also be supplied as arguments to this function.

Details

Creates a plot of a clustering tree given a twins object. The leaves of the tree are the original observations. In case of an agglomerative clustering, two branches come together at the distance between the two clusters being merged. For a divisive clustering, a branch splits up at the diameter of the cluster being splitted.

Note that currently the method function simply calls plot(as.hclust(x), ...), which dispatches to plot.hclust(..). If more flexible plots are needed, consider xx <- as.dendrogram(as.hclust(x)) and plotting xx, see plot.dendrogram.

Value

a NULL value is returned.

See Also

agnes, agnes.object, diana, diana.object, hclust, par, plot.agnes, plot.diana.

Examples

data(votes.repub)
agn <- agnes(votes.repub)
pltree(agn)

dagn  <- as.dendrogram(as.hclust(agn))
dagn2 <- as.dendrogram(as.hclust(agn), hang = 0.2)
op <- par(mar = par("mar") + c(0,0,0, 2)) # more space to the right
plot(dagn2, horiz = TRUE)
plot(dagn, horiz = TRUE, center = TRUE,
     nodePar = list(lab.cex = 0.6, lab.col = "forest green", pch = NA),
     main = deparse(agn$call))
par(op)

cluster documentation built on Nov. 28, 2023, 1:07 a.m.