Uses of Interface
org.ddogleg.clustering.kmeans.InitializeKMeans

Packages that use InitializeKMeans

Package	Description
org.ddogleg.clustering.kmeans

Uses of InitializeKMeans in org.ddogleg.clustering.kmeans

Classes in org.ddogleg.clustering.kmeans that implement InitializeKMeans

Modifier and Type	Class	Description
class	InitializePlusPlus<P>	Implementation of the seeding strategy described in [1].
class	InitializePlusPlus_MT<P>	Concurrent implementation of InitializePlusPlus
class	InitializeStandard<P>	Seeds are selects by randomly picking points.

Fields in org.ddogleg.clustering.kmeans declared as InitializeKMeans

Modifier and Type	Field	Description
InitializeKMeans<P>	StandardKMeans.seedSelector

Methods in org.ddogleg.clustering.kmeans that return InitializeKMeans

Modifier and Type	Method	Description
InitializeKMeans<P>	InitializeKMeans.newInstanceThread()	Creates a new instance which has the same configuration and can be run in parallel.
InitializeKMeans<P>	InitializePlusPlus_MT.newInstanceThread()
InitializeKMeans<P>	InitializePlusPlus.newInstanceThread()
InitializeKMeans<P>	InitializeStandard.newInstanceThread()

Constructors in org.ddogleg.clustering.kmeans with parameters of type InitializeKMeans

Modifier	Constructor	Description
	StandardKMeans(ComputeMeanClusters<P> updateMeans, InitializeKMeans<P> seedSelector, PointDistance<P> distancer, DogLambdas.NewInstance<P> factory)	Configures k-means parameters
	StandardKMeans_MT(ComputeMeanClusters<P> updateMeans, InitializeKMeans<P> seedSelector, PointDistance<P> distancer, DogLambdas.NewInstance<P> factory)	Configures k-means parameters