calinhara: Calinski-Harabasz index

In fpc: Flexible Procedures for Clustering

Calinski-Harabasz index

Description

Calinski-Harabasz index for estimating the number of clusters, based on an observations/variables-matrix here. A distance based version is available through cluster.stats.

Usage

  calinhara(x,clustering,cn=max(clustering))

Arguments

x	data matrix or data frame.
clustering	vector of integers. Clustering.
cn	integer. Number of clusters.

Value

Calinski-Harabasz statistic, which is (n-cn)*sum(diag(B))/((cn-1)*sum(diag(W))). B being the between-cluster means, and W being the within-clusters covariance matrix.

Author(s)

Christian Hennig [e-mail] https://www.unibo.it/sitoweb/christian.hennig/en

References

Calinski, T., and Harabasz, J. (1974) A Dendrite Method for Cluster Analysis, Communications in Statistics, 3, 1-27.

See Also

cluster.stats

Examples

  set.seed(98765)
  iriss <- iris[sample(150,20),-5]
  km <- kmeans(iriss,3)
  round(calinhara(iriss,km$cluster),digits=2)

fpc documentation built on Sept. 24, 2024, 9:07 a.m.