diceR (version 3.0.0)

compactness: Compactness Measure

Description

Compute the compactness validity index for a clustering result.

Usage

compactness(data, labels)

Value

the compactness score

Arguments

data

a dataset with rows as observations, columns as variables

labels

a vector of cluster labels from a clustering result

Author

Derek Chiu

Details

This index is agnostic to any reference clustering results, calculating cluster performance on the basis of compactness and separability. Smaller values indicate a better clustering structure.

References

MATLAB function valid_compactness by Simon Garrett in LinkCluE

Examples

set.seed(1)
E <- matrix(rep(sample(1:4, 1000, replace = TRUE)), nrow = 100, byrow =
              FALSE)
set.seed(1)
dat <- as.data.frame(matrix(runif(1000, -10, 10), nrow = 100, byrow = FALSE))
compactness(dat, E[, 1])