| Package | Description |
|---|---|
| de.lmu.ifi.dbs.elki.algorithm.clustering.em |
Expectation-Maximization clustering algorithm.
|
| de.lmu.ifi.dbs.elki.algorithm.clustering.subspace |
Axis-parallel subspace clustering algorithms
The clustering algorithms in this package are instances of both, projected clustering algorithms or
subspace clustering algorithms according to the classical but somewhat obsolete classification schema
of clustering algorithms for axis-parallel subspaces.
|
| de.lmu.ifi.dbs.elki.algorithm.outlier.clustering |
Clustering based outlier detection.
|
| Class and Description |
|---|
| AbstractEMModelFactory
Abstract base class for initializing EM.
|
| AbstractEMModelFactory.Parameterizer
Parameterization class.
|
| DiagonalGaussianModel
Simpler model for a single Gaussian cluster, without covariances.
|
| DiagonalGaussianModelFactory
Factory for EM with multivariate gaussian models using diagonal matrixes.
|
| EM
Clustering by expectation maximization (EM-Algorithm), also known as Gaussian
Mixture Modeling (GMM).
|
| EMClusterModel
Models useable in EM clustering.
|
| EMClusterModelFactory
Factory for initializing the EM models.
|
| MultivariateGaussianModel
Model for a single Gaussian cluster.
|
| MultivariateGaussianModelFactory
Factory for EM with multivariate gaussian models (with covariance; also known
as Gaussian Mixture Modeling, GMM).
|
| SphericalGaussianModel
Simple spherical Gaussian cluster.
|
| SphericalGaussianModelFactory
Factory for EM with multivariate gaussian models using diagonal matrixes.
|
| Class and Description |
|---|
| MultivariateGaussianModel
Model for a single Gaussian cluster.
|
| Class and Description |
|---|
| EM
Clustering by expectation maximization (EM-Algorithm), also known as Gaussian
Mixture Modeling (GMM).
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.