Uses of Enum Class
org.tribuo.clustering.kmeans.KMeansTrainer.Initialisation

Packages that use KMeansTrainer.Initialisation

Package	Description
org.tribuo.clustering.kmeans	Provides a multithreaded implementation of K-Means, with a configurable distance function.

Uses of KMeansTrainer.Initialisation in org.tribuo.clustering.kmeans

Fields in org.tribuo.clustering.kmeans declared as KMeansTrainer.Initialisation

Modifier and Type	Field	Description
KMeansTrainer.Initialisation	KMeansOptions.initialisation	Initialisation function in K-Means.
KMeansTrainer.Initialisation	TrainTest.KMeansOptions.initialisation	Type of initialisation to use for centroids.

Methods in org.tribuo.clustering.kmeans that return KMeansTrainer.Initialisation

Modifier and Type	Method	Description
static KMeansTrainer.Initialisation	KMeansTrainer.Initialisation.valueOf(String name)	Returns the enum constant of this class with the specified name.
static KMeansTrainer.Initialisation[]	KMeansTrainer.Initialisation.values()	Returns an array containing the constants of this enum class, in the order they are declared.

Constructors in org.tribuo.clustering.kmeans with parameters of type KMeansTrainer.Initialisation

Modifier	Constructor	Description
	KMeansTrainer(int centroids, int iterations, KMeansTrainer.Distance distanceType, KMeansTrainer.Initialisation initialisationType, int numThreads, long seed)	Constructs a K-Means trainer using the supplied parameters.