Uses of Class
de.lmu.ifi.dbs.elki.data.Cluster

Packages that use Cluster

de.lmu.ifi.dbs.elki.algorithm.clustering	Clustering algorithms Clustering algorithms are supposed to implement the Algorithm-Interface.
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation	Correlation clustering algorithms
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.data	Basic classes for different data types, database object types and label types.
de.lmu.ifi.dbs.elki.evaluation.paircounting.generator	Pair generation for pair counting evaluation.
de.lmu.ifi.dbs.elki.evaluation.roc	Evaluation of rankings using ROC AUC (Receiver Operation Characteristics - Area Under Curve)
de.lmu.ifi.dbs.elki.result.textwriter	Text serialization (CSV, Gnuplot, Console, ...)
de.lmu.ifi.dbs.elki.result.textwriter.naming	Naming schemes for clusters (for output when an algorithm doesn't generate cluster names).
de.lmu.ifi.dbs.elki.visualization.visualizers.optics	Visualizers that do work on OPTICS plots

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

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering that return Cluster

private Cluster<DendrogramModel<D>>	SLINK.createParent(String name, Cluster<DendrogramModel<D>> leftChild, Cluster<DendrogramModel<D>> rightChild, D distance, ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier)
private Cluster<DendrogramModel<D>>	SLINK.lastAncestor(Cluster<DendrogramModel<D>> cluster, ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier) Determines recursively the last ancestor of the specified cluster.
private Cluster<DendrogramModel<D>>	SLINK.root(Map<DBID,ModifiableDBIDs> cluster_ids, Map<DBID,D> cluster_distances, DataStore<DBID> pi, DataStore<D> lambda, ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier, FiniteProgress progress)

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering with parameters of type Cluster

private Cluster<DendrogramModel<D>>	SLINK.createParent(String name, Cluster<DendrogramModel<D>> leftChild, Cluster<DendrogramModel<D>> rightChild, D distance, ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier)
private Cluster<DendrogramModel<D>>	SLINK.createParent(String name, Cluster<DendrogramModel<D>> leftChild, Cluster<DendrogramModel<D>> rightChild, D distance, ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier)
private Cluster<DendrogramModel<D>>	SLINK.lastAncestor(Cluster<DendrogramModel<D>> cluster, ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier) Determines recursively the last ancestor of the specified cluster.

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering with type arguments of type Cluster

private Cluster<DendrogramModel<D>>	SLINK.createParent(String name, Cluster<DendrogramModel<D>> leftChild, Cluster<DendrogramModel<D>> rightChild, D distance, ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier)
private Cluster<DendrogramModel<D>>	SLINK.lastAncestor(Cluster<DendrogramModel<D>> cluster, ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier) Determines recursively the last ancestor of the specified cluster.
private Cluster<DendrogramModel<D>>	SLINK.root(Map<DBID,ModifiableDBIDs> cluster_ids, Map<DBID,D> cluster_distances, DataStore<DBID> pi, DataStore<D> lambda, ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier, FiniteProgress progress)

Uses of Cluster in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation

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

private SortedMap<Integer,List<Cluster<CorrelationModel<V>>>>

ERiC.extractCorrelationClusters(Clustering<Model> copacResult, Relation<V> database, int dimensionality) Extracts the correlation clusters and noise from the copac result and returns a mapping of correlation dimension to maps of clusters within this correlation dimension.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with parameters of type Cluster

private boolean

ERiC.isParent(ERiCDistanceFunction distanceFunction, Cluster<CorrelationModel<V>> parent, List<Cluster<CorrelationModel<V>>> children) Returns true, if the specified parent cluster is a parent of one child of the children clusters.

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with type arguments of type Cluster

private void	ERiC.buildHierarchy(SortedMap<Integer,List<Cluster<CorrelationModel<V>>>> clusterMap, DistanceQuery<V,IntegerDistance> query)
private boolean	ERiC.isParent(ERiCDistanceFunction distanceFunction, Cluster<CorrelationModel<V>> parent, List<Cluster<CorrelationModel<V>>> children) Returns true, if the specified parent cluster is a parent of one child of the children clusters.

Uses of Cluster in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace

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

private List<Cluster<Model>>	SUBCLU.runDBSCAN(Relation<V> relation, DBIDs ids, Subspace<V> subspace) Runs the DBSCAN algorithm on the specified partition of the database in the given subspace.
private List<Cluster<SubspaceModel<V>>>	DiSH.sortClusters(Relation<V> database, Map<BitSet,List<Pair<BitSet,ArrayModifiableDBIDs>>> clustersMap) Returns a sorted list of the clusters w.r.t. the subspace dimensionality in descending order.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace with parameters of type Cluster

private boolean

DiSH.isParent(Relation<V> database, DiSHDistanceFunction.Instance<V> distFunc, Cluster<SubspaceModel<V>> parent, List<Cluster<SubspaceModel<V>>> children) Returns true, if the specified parent cluster is a parent of one child of the children clusters.

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace with type arguments of type Cluster

private Subspace<V>	SUBCLU.bestSubspace(List<Subspace<V>> subspaces, Subspace<V> candidate, TreeMap<Subspace<V>,List<Cluster<Model>>> clusterMap) Determines the d-dimensional subspace of the (d+1) -dimensional candidate with minimal number of objects in the cluster.
private void	DiSH.buildHierarchy(Relation<V> database, DiSHDistanceFunction.Instance<V> distFunc, List<Cluster<SubspaceModel<V>>> clusters, int dimensionality) Builds the cluster hierarchy.
private boolean	DiSH.isParent(Relation<V> database, DiSHDistanceFunction.Instance<V> distFunc, Cluster<SubspaceModel<V>> parent, List<Cluster<SubspaceModel<V>>> children) Returns true, if the specified parent cluster is a parent of one child of the children clusters.

Uses of Cluster in de.lmu.ifi.dbs.elki.data

Fields in de.lmu.ifi.dbs.elki.data with type parameters of type Cluster

private Hierarchy<Cluster<M>>	Cluster.hierarchy Object that the hierarchy management is delegated to.
private List<Cluster<M>>	Clustering.toplevelclusters Keep a list of top level clusters.

Methods in de.lmu.ifi.dbs.elki.data that return types with arguments of type Cluster

List<Cluster<M>>	Clustering.getAllClusters() Collect all clusters (recursively) into a List.
List<Cluster<M>>	Cluster.getChildren() Delegate to hierarchy object
Set<Cluster<M>>	Cluster.getDescendants() Collect descendants
Hierarchy<Cluster<M>>	Cluster.getHierarchy() Get hierarchy object
List<Cluster<M>>	Cluster.getParents() Delegate to hierarchy object
List<Cluster<M>>	Clustering.getToplevelClusters() Return top level clusters
IterableIterator<Cluster<M>>	Cluster.iterAncestors() Delegate to hierarchy object
IterableIterator<Cluster<M>>	Cluster.iterDescendants() Delegate to hierarchy object

Methods in de.lmu.ifi.dbs.elki.data with parameters of type Cluster

void	Clustering.addCluster(Cluster<M> n) Add a cluster to the clustering.
int	Cluster.PartialComparator.compare(Cluster<?> o1, Cluster<?> o2)
int	Cluster.PartialComparator.compare(Cluster<?> o1, Cluster<?> o2)

Method parameters in de.lmu.ifi.dbs.elki.data with type arguments of type Cluster

void	Cluster.setHierarchy(Hierarchy<Cluster<M>> hierarchy) Set hierarchy object

Constructor parameters in de.lmu.ifi.dbs.elki.data with type arguments of type Cluster

Cluster(String name, DBIDs ids, boolean noise, M model, Hierarchy<Cluster<M>> hierarchy)
Full constructor

Cluster(String name, DBIDs ids, boolean noise, M model, List<Cluster<M>> children, List<Cluster<M>> parents)
Constructor with hierarchy information.

Cluster(String name, DBIDs ids, boolean noise, M model, List<Cluster<M>> children, List<Cluster<M>> parents)
Constructor with hierarchy information.

Cluster(String name, DBIDs ids, M model, Hierarchy<Cluster<M>> hierarchy)
Constructor with hierarchy but noise flag defaulting to false.

Cluster(String name, DBIDs ids, M model, List<Cluster<M>> children, List<Cluster<M>> parents)
Constructor with hierarchy information, but no noise flag.

Cluster(String name, DBIDs ids, M model, List<Cluster<M>> children, List<Cluster<M>> parents)
Constructor with hierarchy information, but no noise flag.

Clustering(String name, String shortname, List<Cluster<M>> toplevelclusters)
Constructor with a list of top level clusters

Uses of Cluster in de.lmu.ifi.dbs.elki.evaluation.paircounting.generator

Constructors in de.lmu.ifi.dbs.elki.evaluation.paircounting.generator with parameters of type Cluster

PairGeneratorNoise(Cluster<?> cluster)
Crate new generator for a base cluster object.

PairGeneratorSingleCluster(Cluster<?> cluster, boolean useHierarchical)
Generate pairs for a hierarchical cluster.

Uses of Cluster in de.lmu.ifi.dbs.elki.evaluation.roc

Methods in de.lmu.ifi.dbs.elki.evaluation.roc with parameters of type Cluster

static <D extends Distance<D>> double

ROC.computeROCAUCDistanceResult(int size, Cluster<?> clus, List<DistanceResultPair<D>> nei) Compute a ROC curves Area-under-curve for a QueryResult and a Cluster.

Uses of Cluster in de.lmu.ifi.dbs.elki.result.textwriter

Methods in de.lmu.ifi.dbs.elki.result.textwriter with parameters of type Cluster

private void

TextWriter.writeClusterResult(Database db, StreamFactory streamOpener, Cluster<?> clus, List<Relation<?>> ra, NamingScheme naming, List<SettingsResult> sr)

Uses of Cluster in de.lmu.ifi.dbs.elki.result.textwriter.naming

Fields in de.lmu.ifi.dbs.elki.result.textwriter.naming with type parameters of type Cluster

private Map<Cluster<?>,String>

SimpleEnumeratingScheme.names Assigned cluster names.

Methods in de.lmu.ifi.dbs.elki.result.textwriter.naming with parameters of type Cluster

String	SimpleEnumeratingScheme.getNameFor(Cluster<?> cluster) Retrieve the cluster name.
String	NamingScheme.getNameFor(Cluster<?> cluster) Retrieve a name for the given cluster.

Uses of Cluster in de.lmu.ifi.dbs.elki.visualization.visualizers.optics

Method parameters in de.lmu.ifi.dbs.elki.visualization.visualizers.optics with type arguments of type Cluster

private void

OPTICSClusterVisualization.drawClusters(List<Cluster<OPTICSModel>> clusters, int depth) Recursively draw clusters