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

Packages that use KMeansTrainer.Distance

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

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

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

Modifier and Type	Field	Description
KMeansTrainer.Distance	KMeansOptions.distance	Distance function in K-Means.
KMeansTrainer.Distance	TrainTest.KMeansOptions.distance	Distance function to use in the e step.

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

Modifier and Type	Method	Description
static KMeansTrainer.Distance	KMeansTrainer.Distance.valueOf(String name)	Returns the enum constant of this class with the specified name.
static KMeansTrainer.Distance[]	KMeansTrainer.Distance.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.Distance

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