ClusterDaviesBouldinIndex function

Davies Bouldin Index

Davies Bouldin Index

Internal (i.e. without prior classification) cluster quality measure called Davies Bouldin index for a given clustering published in [Davies/Bouldin, 1979].

ClusterDaviesBouldinIndex(Cls, Data,...)

Arguments

  • Cls: [1:n] numerical vector of numbers defining the classification as the main output of the clustering algorithm for the n cases of data. It has k unique numbers representing the arbitrary labels of the clustering.
  • Data: matrix, [1:d,1:n] dataset of d variables and n cases
  • ...: Further arguments passed on to the index.DB function of clusterSim

Details

Wrapper for index.DB. Davies Bouldin index is defined in [Davies/Bouldin, 1979]. Best clustering scheme essentially minimizes the Davies-Bouldin index because it is defined as the function of the ratio of the within cluster scatter, to the between cluster separation.[Davies/Bouldin, 1979].

Returns

List of - DaviesBouldinIndex: scalar,Davies Bouldin index

  • Object: further information stored in index.DB

References

[Davies/Bouldin, 1979] Davies, D. L., & Bouldin, D. W.: A cluster separation measure, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 1(2), pp. 224-227. doi 10.1109/TPAMI.1979.4766909, 1979.

Author(s)

Michael Thrun

Examples

data("Hepta") Cls=kmeansClustering(Hepta$Data,ClusterNo = 7,Type="Hartigan")$Cls ClusterDaviesBouldinIndex(Cls,Hepta$Data)[1] data("Hepta") ClsWellSeperated=kmeansClustering(Hepta$Data,ClusterNo = 7,Type="Steinley")$Cls ClusterDaviesBouldinIndex(ClsWellSeperated,Hepta$Data)[1]
  • Maintainer: Michael Thrun
  • License: GPL-3
  • Last published: 2023-10-19