Uses of Enum Class
org.tribuo.clustering.kmeans.KMeansTrainer.Initialisation
Packages that use KMeansTrainer.Initialisation
Package
Description
Provides a multithreaded implementation of K-Means, with a
configurable distance function.
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Uses of KMeansTrainer.Initialisation in org.tribuo.clustering.kmeans
Subclasses with type arguments of type KMeansTrainer.Initialisation in org.tribuo.clustering.kmeansModifier and TypeClassDescriptionstatic enumPossible initialization functions.Fields in org.tribuo.clustering.kmeans declared as KMeansTrainer.InitialisationModifier and TypeFieldDescriptionKMeansOptions.initialisationInitialisation function in K-Means.TrainTest.KMeansOptions.initialisationType of initialisation to use for centroids.Methods in org.tribuo.clustering.kmeans that return KMeansTrainer.InitialisationModifier and TypeMethodDescriptionstatic KMeansTrainer.InitialisationReturns 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.InitialisationModifierConstructorDescriptionKMeansTrainer(int centroids, int iterations, KMeansTrainer.Distance distanceType, KMeansTrainer.Initialisation initialisationType, int numThreads, long seed) Constructs a K-Means trainer using the supplied parameters.