sp.kmedoids: k-Medoids Clustering for Data on Hypersphere

In kyoustat/RiemSphere: What the package doesas

Description

k-Medoids Clustering for Data on Hypersphere

Usage

sp.kmedoids(x, k = 2, type = c("intrinsic", "extrinsic"))

Examples

## generate two-cluster data
mymu1 = c(0,0,0,1)  # center of class 1
mymu2 = c(-1,0,0,0) # center of class 2

x1 = rvmf(50, mymu1, kappa=5)
x2 = rvmf(50, mymu2, kappa=10)
xx = rbind(x1,x2)

## apply clustering with different k values
cl2 <- sp.kmedoids(xx, k=2)
cl3 <- sp.kmedoids(xx, k=3)
cl4 <- sp.kmedoids(xx, k=4)

## compute 2-dimensional embedding for visualization
mds2d <- sp.mds(xx, ndim=2)
mdsx  <- mds2d$embed[,1]
mdsy  <- mds2d$embed[,2]

## compare via visualization
opar  <- par(mfrow=c(1,3), pty="s")
plot(mdsx, mdsy, col=cl2$cluster, main="k=2 medoids", pch=19)
plot(mdsx, mdsy, col=cl3$cluster, main="k=3 medoids", pch=19)
plot(mdsx, mdsy, col=cl4$cluster, main="k=4 medoids", pch=19)
par(opar)

kyoustat/RiemSphere documentation built on April 13, 2020, 10:04 a.m.