Uses of Package
elki.clustering.kmeans.initialization

Packages that use elki.clustering.kmeans.initialization Package Description elki.clustering.em.models elki.clustering.kmeans Kmeans clustering and variations.elki.clustering.kmeans.initialization Initialization strategies for kmeans.elki.clustering.kmeans.parallel Parallelized implementations of kmeans.elki.clustering.kmeans.spherical Spherical kmeans clustering and variations.elki.clustering.kmedoids.initialization elki.clustering.uncertain Clustering algorithms for uncertain data.tutorial.clustering Classes from the tutorial on implementing a custom kmeans variation. 
Classes in elki.clustering.kmeans.initialization used by elki.clustering.em.models Class Description KMeansInitialization Interface for initializing KMeans 
Classes in elki.clustering.kmeans.initialization used by elki.clustering.kmeans Class Description KMeansInitialization Interface for initializing KMeansPredefined Run kmeans with prespecified initial means. 
Classes in elki.clustering.kmeans.initialization used by elki.clustering.kmeans.initialization Class Description AbstractKMeansInitialization Abstract base class for common kmeans initializations.AbstractKMeansInitialization.Par Parameterization class.AFKMC2 AFKMC² initializationAFKMC2.Instance Abstract instance implementing the weight handling.AFKMC2.Par Parameterization class.FarthestPoints KMeans initialization by repeatedly choosing the farthest point (by the minimum distance to earlier points).FarthestPoints.Par Parameterization class.FarthestSumPoints KMeans initialization by repeatedly choosing the farthest point (by the sum of distances to previous objects).FirstK Initialize Kmeans by using the first k objects as initial means.KMC2 KMC² initializationKMC2.Instance Abstract instance implementing the weight handling.KMC2.Par Parameterization class.KMeansInitialization Interface for initializing KMeansKMeansPlusPlus KMeans++ initialization for kmeans.KMeansPlusPlus.Instance Abstract instance implementing the weight handling.KMeansPlusPlus.NumberVectorInstance Instance for kmeans, number vector based.Ostrovsky Ostrovsky initial means, a variant of kmeans++ that is expected to give slightly better results on average, but only works for kmeans and not for, e.g., PAM (kmedoids).Predefined Run kmeans with prespecified initial means.RandomlyChosen Initialize Kmeans by randomly choosing k existing elements as initial cluster centers.RandomNormalGenerated Initialize kmeans by generating random vectors (normal distributed with \(N(\mu,\sigma)\) in each dimension).RandomUniformGenerated Initialize kmeans by generating random vectors (uniform, within the value range of the data set).SampleKMeans Initialize kmeans by running kmeans on a sample of the data set only.SphericalAFKMC2 Spherical KMeans++ initialization with markov chains.SphericalKMeansPlusPlus Spherical KMeans++ initialization for kmeans. 
Classes in elki.clustering.kmeans.initialization used by elki.clustering.kmeans.parallel Class Description KMeansInitialization Interface for initializing KMeans 
Classes in elki.clustering.kmeans.initialization used by elki.clustering.kmeans.spherical Class Description KMeansInitialization Interface for initializing KMeans 
Classes in elki.clustering.kmeans.initialization used by elki.clustering.kmedoids.initialization Class Description AbstractKMeansInitialization.Par Parameterization class.KMeansInitialization Interface for initializing KMeans 
Classes in elki.clustering.kmeans.initialization used by elki.clustering.uncertain Class Description KMeansInitialization Interface for initializing KMeans 
Classes in elki.clustering.kmeans.initialization used by tutorial.clustering Class Description KMeansInitialization Interface for initializing KMeans