Uses of Class
de.lmu.ifi.dbs.elki.data.model.MeanModel

Packages that use MeanModel

de.lmu.ifi.dbs.elki.algorithm.clustering	Clustering algorithms Clustering algorithms are supposed to implement the Algorithm-Interface.
de.lmu.ifi.dbs.elki.data.model	Cluster models classes for various algorithms.
de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d	Visualizers based on 2D projections.

Uses of MeanModel in de.lmu.ifi.dbs.elki.algorithm.clustering

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering that return types with arguments of type MeanModel

Clustering<MeanModel<V>>

KMeans.run(Database database, Relation<V> relation) Run k-means

Uses of MeanModel in de.lmu.ifi.dbs.elki.data.model

Subclasses of MeanModel in de.lmu.ifi.dbs.elki.data.model

class	EMModel<V extends FeatureVector<V,?>> Cluster model of an EM cluster, providing a mean and a full covariance Matrix.
class	SubspaceModel<V extends FeatureVector<V,?>> Model for Subspace Clusters.

Uses of MeanModel in de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d

Fields in de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d with type parameters of type MeanModel

(package private) Clustering<MeanModel<NV>>

ClusterMeanVisualization.clustering Clustering to visualize.

Methods in de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d that return types with arguments of type MeanModel

private static <NV extends NumberVector<NV,?>> Clustering<MeanModel<NV>>	ClusterMeanVisualization.Factory.findMeanModel(Clustering<?> c) Test if the given clustering has a mean model.
private static <NV extends NumberVector<NV,?>> Clustering<MeanModel<NV>>	EMClusterVisualization.Factory.findMeanModel(Clustering<?> c) Test if the given clustering has a mean model.