# 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, François-Joseph Lapointe and Vladimir Makarenkov

### See Also

`ClusterStability`

,
`ClusterStability_exact`

,
`Kcombination`

,
`Reorder`

,
`Stirling2nd`