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
 


Release 0.4.0 (2011-09-20_1324)