Uses of 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 and Description
KMeansTrainer.Initialisation	TrainTest.KMeansOptions.initialisation
KMeansTrainer.Initialisation	KMeansOptions.initialisation

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

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

Constructor and 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.