sClust (version 1.0)

HierarchicalClust: Hierarchical 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

Examples

# NOT RUN {
### 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)
# }