Package

weka.clusterers

Synopsis

Cluster data using the FarthestFirst algorithm.

For more information see:

Hochbaum, Shmoys (1985). A best possible heuristic for the k-center problem. Mathematics of Operations Research. 10(2):180-184.

Sanjoy Dasgupta: Performance Guarantees for Hierarchical Clustering. In: 15th Annual Conference on Computational Learning Theory, 351-363, 2002.

Notes:

The table below describes the options available for FarthestFirst.

Option	Description
numClusters	set number of clusters
seed	The random number seed to be used.

The table below describes the capabilites of FarthestFirst.

Capability	Supported
Class	No class
Attributes	Missing values, Date attributes, Unary attributes, Empty nominal attributes, Binary attributes, Nominal attributes, Numeric attributes
Min # of instances	1