Uses of Class
elki.clustering.subspace.P3C.ClusterCandidate

Packages that use P3C.ClusterCandidate

Package	Description
elki.clustering.subspace	Axis-parallel subspace clustering algorithms.

Uses of P3C.ClusterCandidate in elki.clustering.subspace

Methods in elki.clustering.subspace that return types with arguments of type P3C.ClusterCandidate

Modifier and Type	Method	Description
private java.util.ArrayList<P3C.ClusterCandidate>	P3C.hardClustering(WritableDataStore<double[]> probClusterIGivenX, java.util.List<P3C.Signature> clusterCores, DBIDs dbids)	Creates a hard clustering from the specified soft membership matrix.

Method parameters in elki.clustering.subspace with type arguments of type P3C.ClusterCandidate

Modifier and Type	Method	Description
private void	P3C.findOutliers(Relation<? extends NumberVector> relation, java.util.List<MultivariateGaussianModel> models, java.util.ArrayList<P3C.ClusterCandidate> clusterCandidates, ModifiableDBIDs noise)	Performs outlier detection by testing the Mahalanobis distance of each point in a cluster against the critical value of the ChiSquared distribution with as many degrees of freedom as the cluster has relevant attributes.