Uses of Interface
elki.clustering.em.models.BetulaClusterModel

Packages that use BetulaClusterModel

Package	Description
elki.clustering.em	Expectation-Maximization clustering algorithm for Gaussian Mixture Modeling (GMM).
elki.clustering.em.models

Uses of BetulaClusterModel in elki.clustering.em

Method parameters in elki.clustering.em with type arguments of type BetulaClusterModel

Modifier and Type	Method	Description
double	BetulaGMM.assignProbabilitiesToInstances(Relation<? extends NumberVector> relation, java.util.List<? extends BetulaClusterModel> models, WritableDataStore<double[]> probClusterIGivenX)	Assigns the current probability values to the instances in the database and compute the expectation value of the current mixture of distributions.
double	BetulaGMM.assignProbabilitiesToInstances(java.util.ArrayList<? extends ClusterFeature> cfs, java.util.List<? extends BetulaClusterModel> models, java.util.Map<ClusterFeature,double[]> probClusterIGivenX)	Assigns the current probability values to the instances in the database and compute the expectation value of the current mixture of distributions.
double	BetulaGMMWeighted.assignProbabilitiesToInstances(java.util.ArrayList<? extends ClusterFeature> cfs, java.util.List<? extends BetulaClusterModel> models, java.util.Map<ClusterFeature,double[]> probClusterIGivenX)
void	BetulaGMM.recomputeCovarianceMatrices(java.util.ArrayList<? extends ClusterFeature> cfs, java.util.Map<ClusterFeature,double[]> probClusterIGivenX, java.util.List<? extends BetulaClusterModel> models, double prior, int n)	Recompute the covariance matrixes.

Uses of BetulaClusterModel in elki.clustering.em.models

Classes in elki.clustering.em.models with type parameters of type BetulaClusterModel

Modifier and Type	Interface	Description
interface	BetulaClusterModelFactory<M extends BetulaClusterModel>	Factory for initializing the EM models.

Classes in elki.clustering.em.models that implement BetulaClusterModel

Modifier and Type	Class	Description
class	DiagonalGaussianModel	Simpler model for a single Gaussian cluster, without covariances.
class	MultivariateGaussianModel	Model for a single multivariate Gaussian cluster with arbitrary rotation.
class	SphericalGaussianModel	Simple spherical Gaussian cluster (scaled identity matrixes).