HierarchicalClust: Hierarchical Clustering

In sClust: R Toolbox for Unsupervised Spectral Clustering

Description

Hierarchical Clustering

Usage

HierarchicalClust(
  W,
  K = 5,
  method = "ward.D2",
  flagDiagZero = FALSE,
  verbose = FALSE,
  ...
)

Arguments

W	Gram Similarity Matrix.
K	number of cluster to obtain.
method	method that will be used in the hierarchical clustering.
flagDiagZero	if True, Put zero on the similarity matrix W.
verbose	To output the verbose in the terminal.
...	Additional parameter for the hclust function.

Value

returns a list containing the following elements:

• cluster: a vector containing the cluster

Author(s)

Emilie Poisson Caillault and Erwan Vincent

Examples

### Example 1: 2 disks of the same size
n<-100 ; r1<-1
x<-(runif(n)-0.5)*2;
y<-(runif(n)-0.5)*2
keep1<-which((x*2+y*2)<(r1*2))
disk1<-data.frame(x+3*r1,y)[keep1,]
disk2 <-data.frame(x-3*r1,y)[keep1,]
sameTwoDisks <- rbind(disk1,disk2)
W <- compute.similarity.ZP(scale(sameTwoDisks))
res <- HierarchicalClust(W,K=2,method="ward.D2",flagDiagZero=TRUE,verbose=TRUE)
plot(sameTwoDisks, col = res$cluster)

### Example 2: Speed and Stopping Distances of Cars
W <- compute.similarity.ZP(scale(iris[,-5]))
res <- HierarchicalClust(W,K=2,method="ward.D2",flagDiagZero=TRUE,verbose=TRUE)
plot(iris, col = res$cluster)

sClust documentation built on Aug. 24, 2021, 1:06 a.m.