Uses of Interface
edu.ucla.sspace.clustering.seeding.KMeansSeed

Packages that use KMeansSeed

Package	Description
edu.ucla.sspace.clustering
edu.ucla.sspace.clustering.seeding

Uses of KMeansSeed in edu.ucla.sspace.clustering

Methods in edu.ucla.sspace.clustering with parameters of type KMeansSeed

Modifier and Type	Method and Description
static Assignments	DirectClustering.cluster(Matrix matrix, int numClusters, int numRepetitions, KMeansSeed seedType, CriterionFunction criterion) Clusters matrix using the specified SeedAlgorithm and the specified CriterionFunction.

Uses of KMeansSeed in edu.ucla.sspace.clustering.seeding

Classes in edu.ucla.sspace.clustering.seeding that implement KMeansSeed

Modifier and Type	Class and Description
class	GeneralizedOrssSeed A utility class for selected k data points as seeds from a list of n >> k data points using a general method for comparing the similarity (distance) of data points.
class	KMeansPlusPlusSeed This KMeansSeed implementation attempts to select centroids from the set of data points that are well scattered.
class	OrssSeed Select seeds using a modification of the ORSS algorithm.
class	RandomSeed This KMeansSeed implementation selects data points at random from any given data set to serve as the initial centroid seeds.