Assessment of the stability of individual objects, clusters and a whole clustering solution based on repeated runs of a clustering algorithm.

Description

The ClusterStability package uses a probabilistic framework and some well-known clustering criteria (e.g. Calinski-Harabasz, Silhouette, Dunn and Davies-Bouldin) to compute the stability scores (ST) of each individual object (i.e., element) in the clustering solution provided by the K-means and K-medoids partitioning algorithms.

Details

Package: ClusterStability
Type: Package
Version: 1.0.2
Date: 2015-10-14
License: GPL-2
Maintainer: Etienne Lord <m.etienne.lord@gmail.com>,
Vladimir Makarenkov <makarenkov.vladimir@uqam.ca>

Function ClusterStability computes the individual and global stability scores (ST) for a partitioning solution using either K-means or K-medoids (the approximate solution is provided).

Function ClusterStability_exact is similar to the ClusterStability function but uses the Stirling numbers of the second kind to compute the exact stability scores (but is limited to a small number of objects).

Function Kcombination computes the k-combination of a set of numbers for a given k.

Function Reorder returns the re-ordered partitioning of a series of clusters.

Function Stirling2nd computes the Stirling numbers of the second kind.

Author(s)

Etienne Lord, Fran├žois-Joseph Lapointe and Vladimir Makarenkov

See Also

ClusterStability, ClusterStability_exact, Kcombination, Reorder, Stirling2nd