protoclust-package: Hierarchical Clustering with Prototypes: Minimax Linkage.

In protoclust: Hierarchical Clustering with Prototypes

Hierarchical Clustering with Prototypes: Minimax Linkage.

Description

Functions to perform minimax linkage hierarchical clustering and to cut such trees to return clusterings with prototypes.

Details

Package:	protoclust
Type:	Package
Version:	1.0
Date:	2011-06-21
License:	GPL-2
LazyLoad:	yes

Author(s)

Jacob Bien and Rob Tibshirani

Maintainer: Jacob Bien <[e-mail]>

References

Bien, J., and Tibshirani, R. (2011), "Hierarchical Clustering with Prototypes via Minimax Linkage," The Journal of the American Statistical Association, 106(495), 1075-1084.

See Also

protoclust, protocut, plotwithprototypes

Examples

# generate some data:
set.seed(1)
n <- 100
p <- 2
x <- matrix(rnorm(n * p), n, p)
rownames(x) <- paste("A", 1:n, sep="")
d <- dist(x)

# perform minimax linkage clustering:
hc <- protoclust(d)

# cut the tree to yield a 10-cluster clustering:
k <- 10 # number of clusters
cut <- protocut(hc, k=k)
h <- hc$height[n - k]

# plot dendrogram (and show cut):
plotwithprototypes(hc, imerge=cut$imerge, col=2)
abline(h=h, lty=2)

# get the prototype assigned to each point:
pr <- cut$protos[cut$cl]

# find point farthest from its prototype:
dmat <- as.matrix(d)
ifar <- which.max(dmat[cbind(1:n, pr[1:n])])

# note that this distance is exactly h:
stopifnot(dmat[ifar, pr[ifar]] == h)

# since this is a 2d example, make 2d display:
plot(x, type="n")
points(x, pch=20, col="lightblue")
lines(rbind(x[ifar, ], x[pr[ifar], ]), col=3)
points(x[cut$protos, ], pch=20, col="red")
text(x[cut$protos, ], labels=hc$labels[cut$protos], pch=19)
tt <- seq(0, 2 * pi, length=100)
for (i in cut$protos) {
  lines(x[i, 1] + h * cos(tt), x[i, 2] + h * sin(tt))
}

protoclust documentation built on April 1, 2022, 9:06 a.m.