findPartition

Obtain partitions of the data into k=1,...,Kmax clusters gives the clustering method, distance measure, and other parameters to be used in the clustering

findPartition(X, Kmax, dX = NULL, ...)

Arguments

X

of values

Kmax

max number of clusters

dX

distance measure

...

extra values to be given

Value

list of cluster labels

Examples

example_dta<-create_example_data_for_R()
X=as.matrix(example_dta$counts)
#Default ... values:
default.par <- list(q=0.25,Kmax.rec=5,B=100,ref.gen="PC",dist.method="euclidean",cl.method="hclust",linkage="average",cor.method="pearson",nstart=10)
#Check for user modifications:
fixed.par <- c(minDist=NULL,minSize=2,modifyList(default.par,list(cor.method='pearson',linkage='average')))
#Find stopping threshold if minDist is NULL
minDist <- get.threshold(X,q=fixed.par$q,fixed.par)
fixed.par$minDist <- minDist
cl.lab <- findPartition(X=X,Kmax=10,dX=NULL,fixed.par)