Uses of Class
weka.clusterers.RandomizableClusterer

Packages that use RandomizableClusterer

weka.clusterers

Uses of RandomizableClusterer in weka.clusterers

Subclasses of RandomizableClusterer in weka.clusterers

class	Cobweb Class implementing the Cobweb and Classit clustering algorithms. Note: the application of node operators (merging, splitting etc.) in terms of ordering and priority differs (and is somewhat ambiguous) between the original Cobweb and Classit papers.
class	FarthestFirst Cluster data using the FarthestFirst algorithm. For more information see: Hochbaum, Shmoys (1985).
class	sIB Cluster data using the sequential information bottleneck algorithm. Note: only hard clustering scheme is supported.
class	SimpleKMeans Cluster data using the k means algorithm Valid options are:
class	XMeans Cluster data using the X-means algorithm. X-Means is K-Means extended by an Improve-Structure part In this part of the algorithm the centers are attempted to be split in its region.