CPS: CPS Analysis on a collection of clustering results

Description Usage Arguments Value Examples

Description

Covering Point Set Analysis of given clustering results. It conducts alignment among different results and then calculates the covering point set. The return contains several statistics which can be directly used as input for mplot or cplot. By using this function you can design your own workflow instead od using clustCPS, see vignette for more destails.

Usage

1
CPS(ref, vis, pert)

Arguments

ref

– the reference clustering result, the first cluster is labeled as 1.

vis

– the visualization coordinates.

pert

– a collection of clustering results in a matrix format, each column represents one clustering result.

Value

a list used for mplot or cplot, in which tight_all is the overall tightness, member is the matrix used for the membership heat map, set is the matrix for the covering point set plot, tight is the vector of cluster-wise tightness, vis is the visualization coordinates, and ref is the reference labels.

Examples

1
2
3
4
5
6
7
8
9
# CPS analysis on selection of visualization methods
data(vis_pollen)
k1=kmeans(vis_pollen$vis,max(vis_pollen$ref))$cluster
k2=kmeans(vis_pollen$vis,max(vis_pollen$ref))$cluster
k=cbind(as.matrix(k1,ncol=1),as.matrix(k2,ncol=1))
c=CPS(vis_pollen$ref, vis_pollen$vis, pert=k)
# visualization of the results
mplot(c,2)
cplot(c,2)

OTclust documentation built on May 6, 2019, 9 a.m.