Uses of 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 and Description
KMeansTrainer.Distance	TrainTest.KMeansOptions.distance
KMeansTrainer.Distance	KMeansOptions.distance

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

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

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

Constructor and 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.