@Title("EM (Gaussian Mixture Modeling with Expectation Maximization)")

Package elki.clustering.em

Expectation-Maximization clustering algorithm for Gaussian Mixture Modeling (GMM).
• Class Summary
Class Description
BetulaGMM
Clustering by expectation maximization (EM-Algorithm), also known as Gaussian Mixture Modeling (GMM), with optional MAP regularization.
BetulaGMM.Par
Parameterizer
BetulaGMMWeighted
Clustering by expectation maximization (EM-Algorithm), also known as Gaussian Mixture Modeling (GMM), with optional MAP regularization.
BetulaGMMWeighted.Par
Parameterizer
EM<O,​M extends MeanModel>
Clustering by expectation maximization (EM-Algorithm), also known as Gaussian Mixture Modeling (GMM), with optional MAP regularization.
EM.Par<O,​M extends MeanModel>
Parameterization class.
KDTreeEM
Clustering by expectation maximization (EM-Algorithm), also known as Gaussian Mixture Modeling (GMM), calculated on a kd-tree.
KDTreeEM.KDTree
KDTree class with the statistics needed for EM clustering.
KDTreeEM.Par
Parameterization class.