cdbw: CDbw-index for cluster validation

In fpc: Flexible Procedures for Clustering

CDbw-index for cluster validation

Description

CDbw-index for cluster validation, as defined in Halkidi and Vazirgiannis (2008), Halkidi et al. (2015).

Usage

cdbw(x,clustering,r=10,s=seq(0.1,0.8,by=0.1),
                 clusterstdev=TRUE,trace=FALSE)

Arguments

x	something that can be coerced into a numerical matrix. Euclidean dataset.
clustering	vector of integers with length =nrow(x); indicating the cluster for each observation.
r	integer. Number of cluster border representatives.
s	numerical vector of shrinking factors (between 0 and 1).
clusterstdev	logical. If TRUE, the neighborhood radius for intra-cluster density is the within-cluster estimated squared distance from the mean of the cluster; otherwise it is the average of these over all clusters.
trace	logical. If TRUE, results are printed for the steps to compute the index.

Value

List with components (see Halkidi and Vazirgiannis (2008), Halkidi et al. (2015) for details)

cdbw	value of CDbw index (the higher the better).
cohesion	cohesion.
compactness	compactness.
sep	separation.

Author(s)

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

References

Halkidi, M. and Vazirgiannis, M. (2008) A density-based cluster validity approach using multi-representatives. Pattern Recognition Letters 29, 773-786.

Halkidi, M., Vazirgiannis, M. and Hennig, C. (2015) Method-independent indices for cluster validation. In C. Hennig, M. Meila, F. Murtagh, R. Rocci (eds.) Handbook of Cluster Analysis, CRC Press/Taylor & Francis, Boca Raton.

Examples

  options(digits=3)
  iriss <- as.matrix(iris[c(1:5,51:55,101:105),-5])
  irisc <- as.numeric(iris[c(1:5,51:55,101:105),5])
  cdbw(iriss,irisc)

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