Clustering-class

Clustering

Monitor and trace changes in clustering solutions of accumulating datasets
at successive time points. The clusters can adopt External and Internal transition at
succeeding time points. The External transitions comprise of Survived, Merged, Split,
Disappeared, and newly Emerged candidates. In contrast, Internal transition includes changes
in location and cohesion of the survived clusters. The package uses MONIC framework developed by
Spiliopoulou, Ntoutsi, Theodoridis, and Schult (2006)<doi:10.1145/1150402.1150491> .

Muhammad Atif

clusTransition

Monitor Changes in Cluster Solutions of Dynamic Datasets

Clustering-class function

<dl class="dl-horizontal">
<dt><code>Cluster</code></dt><dd>List of matrices, where each element of the list include data items belonging to the corresponding cluster.</dd></dl><dt><code>Centers</code></dt><dd>Matrix of cluster centers.</dd><dt><code>k</code></dt><dd>Number of centers.</dd><dt><code>clusterMem</code></dt><dd>Numeric vector of cluster membership.</dd>

Clustering-class: Class Clustering

Description

Arguments

Slots

Details