Environment for
DeveLoping
KDD-Applications
Supported by Index-Structures

Uses of Interface
de.lmu.ifi.dbs.elki.algorithm.result.clustering.ClusteringResult

Packages that use ClusteringResult
de.lmu.ifi.dbs.elki.algorithm.clustering Package collects clustering algorithms. 
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation Package to collect correlation clustering algorithms suitable as a task for the KDDTask main routine. 
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace Package to collect algorithms for clustering in axis-parallel subspaces, suitable as a task for the KDDTask main routine. 
de.lmu.ifi.dbs.elki.algorithm.result.clustering Package to collect result classes for the results of clustering algorithms. 
 

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

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering that return ClusteringResult
 ClusteringResult<O> Clustering.getResult()
           
 

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

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation that return ClusteringResult
 ClusteringResult<V> COPAC.getResult()
           
 

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

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace that return ClusteringResult
 ClusteringResult<V> CLIQUE.getResult()
          Returns the result of the algorithm.
 

Uses of ClusteringResult in de.lmu.ifi.dbs.elki.algorithm.result.clustering
 

Classes in de.lmu.ifi.dbs.elki.algorithm.result.clustering that implement ClusteringResult
 class Clusters<O extends DatabaseObject>
          Provides a result of a clustering-algorithm that computes several clusters.
 class ClustersPlusNoise<O extends DatabaseObject>
          Provides a result of a clustering-algorithm that computes several clusters and remaining noise.
 class ClustersPlusNoisePlusCorrelationAnalysis<V extends RealVector<V,?>>
          Provides a result of a clustering-algorithm that computes several clusters and remaining noise and a correlation analysis for each cluster.
 class EMClusters<V extends RealVector<V,?>>
          // todo arthur comment
 class PartitionClusteringResults<O extends DatabaseObject>
          A result for a partitioning clustering algorithm providing a single result for a single partition.
 

Fields in de.lmu.ifi.dbs.elki.algorithm.result.clustering with type parameters of type ClusteringResult
private  Map<Integer,ClusteringResult<O>> PartitionClusteringResults.partitionResults
          Holds the results for the partitions.
 

Methods in de.lmu.ifi.dbs.elki.algorithm.result.clustering that return ClusteringResult
 ClusteringResult<O> PartitionClusteringResults.getResult(Integer partitionID)
          Returns the result of the specified partition.
 

Constructor parameters in de.lmu.ifi.dbs.elki.algorithm.result.clustering with type arguments of type ClusteringResult
PartitionClusteringResults(Database<O> db, Map<Integer,ClusteringResult<O>> resultMap, Integer noise)
          A result for a partitioning algorithm providing a single result for a single partition.
 


Release 0.1 (2008-07-10_1838)