Uses of Class
elki.clustering.subspace.P3C.ClusterCandidate
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Packages that use P3C.ClusterCandidate Package Description elki.clustering.subspace Axis-parallel subspace clustering algorithms. -
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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.
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