Davis-Bouldin-Index

Description

Computes the Davis-Bouldin-Index for cluster validation purposes.

Usage

DBIndex(data, labels)

Arguments

Details

To compute a clusters' compactness, this version uses the Euclidean distance to determine the mean distances between the samples and the cluster centers. Furthermore, the distance of two clusters is given by the distance of their centers.

Value

'DBIndex' returns the Davis-Bouldin cluster index, a numeric value.

Author(s)

Christoph Bartenhagen

Examples

## DB-Index of a 50 dimensional dataset with 20 samples separated into two classes
d = generateData(samples=20, genes=50, diffgenes=10, blocksize=5)
DBIndex (data=d[[1]], labels=d[[2]])

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(RDRToolbox)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/RDRToolbox/DBIndex.Rd_%03d_medium.png", width=480, height=480)
> ### Name: DBIndex
> ### Title: Davis-Bouldin-Index
> ### Aliases: DBIndex
> 
> ### ** Examples
> 
> ## DB-Index of a 50 dimensional dataset with 20 samples separated into two classes
> d = generateData(samples=20, genes=50, diffgenes=10, blocksize=5)
> DBIndex (data=d[[1]], labels=d[[2]])
[1] 3.710458
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>