Environment for
DeveLoping
KDD-Applications
Supported by Index-Structures

Uses of Class
de.lmu.ifi.dbs.elki.database.DistanceResultPair

Packages that use DistanceResultPair
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.database ELKI database layer - loading, storing, indexing and accessing data 
de.lmu.ifi.dbs.elki.evaluation.roc Evaluation of rankings using ROC AUC (Receiver Operation Characteristics - Area Under Curve) 
de.lmu.ifi.dbs.elki.index.tree.metrical Tree-based index structures for metrical vector spaces. 
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants M-Tree and variants. 
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp MkAppTree 
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop MkCoPTree 
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax MkMaxTree 
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab MkTabTree 
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree MTree 
de.lmu.ifi.dbs.elki.index.tree.spatial Tree-based index structures for spatial indexing. 
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants R*-Tree and variants. 
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn RdKNNTree 
de.lmu.ifi.dbs.elki.math.linearalgebra.pca Principal Component Analysis (PCA) and Eigenvector processing. 
de.lmu.ifi.dbs.elki.preprocessing Preprocessors used for data preparation in a first step of various algorithms or distance and similarity measures. 
 

Uses of DistanceResultPair 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 DistanceResultPair
private  Map<Integer,List<DistanceResultPair<DoubleDistance>>> PROCLUS.getLocalities(Set<Integer> m_c, Database<V> database)
          Computes the localities of the specified medoids.
 

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

Fields in de.lmu.ifi.dbs.elki.data with type parameters of type DistanceResultPair
private  SortedSet<DistanceResultPair<D>> KNNList.list
          The underlying set.
 

Methods in de.lmu.ifi.dbs.elki.data that return types with arguments of type DistanceResultPair
 List<DistanceResultPair<D>> KNNList.toList()
          Returns a list representation of this KList.
 

Methods in de.lmu.ifi.dbs.elki.data with parameters of type DistanceResultPair
 boolean KNNList.add(DistanceResultPair<D> o)
          Adds a new object to this list.
 

Uses of DistanceResultPair in de.lmu.ifi.dbs.elki.database
 

Methods in de.lmu.ifi.dbs.elki.database that return types with arguments of type DistanceResultPair
<D extends Distance<D>>
List<List<DistanceResultPair<D>>>
Database.bulkKNNQueryForID(List<Integer> ids, int k, DistanceFunction<O,D> distanceFunction)
          Performs k-nearest neighbor queries for the given object IDs.
<D extends Distance<D>>
List<List<DistanceResultPair<D>>>
SequentialDatabase.bulkKNNQueryForID(List<Integer> ids, int k, DistanceFunction<O,D> distanceFunction)
          Retrieves the k nearest neighbors for the query objects.
<D extends Distance<D>>
List<List<DistanceResultPair<D>>>
SpatialIndexDatabase.bulkKNNQueryForID(List<Integer> ids, int k, DistanceFunction<O,D> distanceFunction)
           
<T extends Distance<T>>
List<List<DistanceResultPair<T>>>
MetricalIndexDatabase.bulkKNNQueryForID(List<Integer> ids, int k, DistanceFunction<O,T> distanceFunction)
           
<D extends Distance<D>>
List<DistanceResultPair<D>>
Database.kNNQueryForID(Integer id, int k, DistanceFunction<O,D> distanceFunction)
          Performs a k-nearest neighbor query for the given object ID.
<D extends Distance<D>>
List<DistanceResultPair<D>>
SequentialDatabase.kNNQueryForID(Integer id, int k, DistanceFunction<O,D> distanceFunction)
          Retrieves the k nearest neighbors for the query object.
<D extends Distance<D>>
List<DistanceResultPair<D>>
SpatialIndexDatabase.kNNQueryForID(Integer id, int k, DistanceFunction<O,D> distanceFunction)
           
<T extends Distance<T>>
List<DistanceResultPair<T>>
MetricalIndexDatabase.kNNQueryForID(Integer id, int k, DistanceFunction<O,T> distanceFunction)
           
<D extends Distance<D>>
List<DistanceResultPair<D>>
Database.kNNQueryForObject(O queryObject, int k, DistanceFunction<O,D> distanceFunction)
          Performs a k-nearest neighbor query for the given object.
<D extends Distance<D>>
List<DistanceResultPair<D>>
SequentialDatabase.kNNQueryForObject(O queryObject, int k, DistanceFunction<O,D> distanceFunction)
          Retrieves the k nearest neighbors for the query object.
<D extends Distance<D>>
List<DistanceResultPair<D>>
SpatialIndexDatabase.kNNQueryForObject(O queryObject, int k, DistanceFunction<O,D> distanceFunction)
           
<T extends Distance<T>>
List<DistanceResultPair<T>>
MetricalIndexDatabase.kNNQueryForObject(O queryObject, int k, DistanceFunction<O,T> distanceFunction)
           
<D extends Distance<D>>
List<DistanceResultPair<D>>
Database.rangeQuery(Integer id, String epsilon, DistanceFunction<O,D> distanceFunction)
          Performs a range query for the given object ID with the given epsilon range and the according distance function.
<D extends Distance<D>>
List<DistanceResultPair<D>>
SequentialDatabase.rangeQuery(Integer id, String epsilon, DistanceFunction<O,D> distanceFunction)
           
<D extends Distance<D>>
List<DistanceResultPair<D>>
SpatialIndexDatabase.rangeQuery(Integer id, String epsilon, DistanceFunction<O,D> distanceFunction)
           
<T extends Distance<T>>
List<DistanceResultPair<T>>
MetricalIndexDatabase.rangeQuery(Integer id, String epsilon, DistanceFunction<O,T> distanceFunction)
           
<D extends Distance<D>>
List<DistanceResultPair<D>>
Database.reverseKNNQuery(Integer id, int k, DistanceFunction<O,D> distanceFunction)
          Performs a reverse k-nearest neighbor query for the given object ID.
<D extends Distance<D>>
List<DistanceResultPair<D>>
SequentialDatabase.reverseKNNQuery(Integer id, int k, DistanceFunction<O,D> distanceFunction)
           
<D extends Distance<D>>
List<DistanceResultPair<D>>
SpatialIndexDatabase.reverseKNNQuery(Integer id, int k, DistanceFunction<O,D> distanceFunction)
          Performs a reverse k-nearest neighbor query for the given object ID.
<T extends Distance<T>>
List<DistanceResultPair<T>>
MetricalIndexDatabase.reverseKNNQuery(Integer id, int k, DistanceFunction<O,T> distanceFunction)
           
 

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

Fields in de.lmu.ifi.dbs.elki.evaluation.roc with type parameters of type DistanceResultPair
private  Iterator<DistanceResultPair<D>> ROC.DistanceResultAdapter.iter
          Original Iterator
 

Method parameters in de.lmu.ifi.dbs.elki.evaluation.roc with type arguments of type DistanceResultPair
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.
static
<D extends Distance<D>>
double
ROC.computeROCAUCDistanceResult(int size, Collection<Integer> ids, List<DistanceResultPair<D>> nei)
          Compute a ROC curves Area-under-curve for a QueryResult and a Cluster.
 

Constructor parameters in de.lmu.ifi.dbs.elki.evaluation.roc with type arguments of type DistanceResultPair
ROC.DistanceResultAdapter(Iterator<DistanceResultPair<D>> iter)
          Constructor
 

Uses of DistanceResultPair in de.lmu.ifi.dbs.elki.index.tree.metrical
 

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical that return types with arguments of type DistanceResultPair
abstract  List<DistanceResultPair<D>> MetricalIndex.kNNQuery(O object, int k)
          Performs a k-nearest neighbor query for the given object with the given parameter k and the according distance function.
abstract  List<DistanceResultPair<D>> MetricalIndex.rangeQuery(O object, String epsilon)
          Performs a range query for the given object with the given epsilon range and the according distance function.
abstract  List<DistanceResultPair<D>> MetricalIndex.reverseKNNQuery(O object, int k)
          Performs a reverse k-nearest neighbor query for the given object ID.
 

Uses of DistanceResultPair in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants
 

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants that return types with arguments of type DistanceResultPair
 List<DistanceResultPair<D>> AbstractMTree.kNNQuery(O object, int k)
           
 List<DistanceResultPair<D>> AbstractMTree.rangeQuery(O object, String epsilon)
           
 

Method parameters in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants with type arguments of type DistanceResultPair
private  void AbstractMTree.doRangeQuery(Integer o_p, N node, Integer q, D r_q, List<DistanceResultPair<D>> result)
          Performs a range query on the specified subtree.
 

Uses of DistanceResultPair in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp
 

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp that return types with arguments of type DistanceResultPair
private  List<DistanceResultPair<D>> MkAppTree.doReverseKNNQuery(int k, Integer q)
          Performs a reverse knn query.
 List<DistanceResultPair<D>> MkAppTree.reverseKNNQuery(O object, int k)
          Performs a reverse k-nearest neighbor query for the given object ID.
 

Uses of DistanceResultPair in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop
 

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop that return types with arguments of type DistanceResultPair
 List<DistanceResultPair<D>> MkCoPTree.reverseKNNQuery(O object, int k)
          Performs a reverse k-nearest neighbor query for the given object ID.
 

Method parameters in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop with type arguments of type DistanceResultPair
private  void MkCoPTree.doReverseKNNQuery(int k, Integer q, List<DistanceResultPair<D>> result, List<Integer> candidates)
          Performs a reverse knn query.
 

Uses of DistanceResultPair in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax
 

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax that return types with arguments of type DistanceResultPair
 List<DistanceResultPair<D>> MkMaxTree.reverseKNNQuery(O object, int k)
          Performs a reverse k-nearest neighbor query for the given object ID.
 

Method parameters in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax with type arguments of type DistanceResultPair
private  void MkMaxTree.doReverseKNNQuery(Integer q, MkMaxTreeNode<O,D> node, MkMaxEntry<D> node_entry, List<DistanceResultPair<D>> result)
          Performs a reverse k-nearest neighbor query in the specified subtree for the given query object with k = AbstractMkTree.k_max.
 

Uses of DistanceResultPair in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab
 

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab that return types with arguments of type DistanceResultPair
 List<DistanceResultPair<D>> MkTabTree.reverseKNNQuery(O object, int k)
           
 

Method parameters in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab with type arguments of type DistanceResultPair
private  void MkTabTree.doReverseKNNQuery(int k, Integer q, MkTabEntry<D> node_entry, MkTabTreeNode<O,D> node, List<DistanceResultPair<D>> result)
          Performs a k-nearest neighbor query in the specified subtree for the given query object and the given parameter k.
 

Uses of DistanceResultPair in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree
 

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree that return types with arguments of type DistanceResultPair
 List<DistanceResultPair<D>> MTree.reverseKNNQuery(O object, int k)
          Throws an UnsupportedOperationException since reverse knn queries are not yet supported by an M-Tree.
 

Uses of DistanceResultPair in de.lmu.ifi.dbs.elki.index.tree.spatial
 

Methods in de.lmu.ifi.dbs.elki.index.tree.spatial that return types with arguments of type DistanceResultPair
abstract
<D extends Distance<D>>
List<List<DistanceResultPair<D>>>
SpatialIndex.bulkKNNQueryForIDs(List<Integer> ids, int k, SpatialDistanceFunction<O,D> distanceFunction)
          Performs a bulk k-nearest neighbor query for the given object IDs.
abstract
<D extends Distance<D>>
List<DistanceResultPair<D>>
SpatialIndex.kNNQuery(O obj, int k, SpatialDistanceFunction<O,D> distanceFunction)
          Performs a k-nearest neighbor query for the given object with the given parameter k and the according distance function.
abstract
<D extends Distance<D>>
List<DistanceResultPair<D>>
SpatialIndex.rangeQuery(O obj, String epsilon, SpatialDistanceFunction<O,D> distanceFunction)
          Performs a range query for the given object with the given epsilon range and the according distance function.
abstract
<D extends Distance<D>>
List<DistanceResultPair<D>>
SpatialIndex.reverseKNNQuery(O object, int k, SpatialDistanceFunction<O,D> distanceFunction)
          Performs a reverse k-nearest neighbor query for the given object ID.
 

Uses of DistanceResultPair in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants
 

Methods in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants that return types with arguments of type DistanceResultPair
<D extends Distance<D>>
List<List<DistanceResultPair<D>>>
AbstractRStarTree.bulkKNNQueryForIDs(List<Integer> ids, int k, SpatialDistanceFunction<O,D> distanceFunction)
          Performs a bulk k-nearest neighbor query for the given object IDs.
<D extends Distance<D>>
List<DistanceResultPair<D>>
AbstractRStarTree.kNNQuery(O object, int k, SpatialDistanceFunction<O,D> distanceFunction)
          Performs a k-nearest neighbor query for the given NumberVector with the given parameter k and the according distance function.
<D extends Distance<D>>
List<DistanceResultPair<D>>
AbstractRStarTree.rangeQuery(O object, String epsilon, SpatialDistanceFunction<O,D> distanceFunction)
          Performs a range query for the given spatial object with the given epsilon range and the according distance function.
<D extends Distance<D>>
List<DistanceResultPair<D>>
AbstractRStarTree.reverseKNNQuery(O object, int k, SpatialDistanceFunction<O,D> distanceFunction)
          Performs a reverse k-nearest neighbor query for the given object ID.
 

Uses of DistanceResultPair in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn
 

Methods in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn that return types with arguments of type DistanceResultPair
<T extends Distance<T>>
List<DistanceResultPair<T>>
RdKNNTree.reverseKNNQuery(O object, int k, SpatialDistanceFunction<O,T> distanceFunction)
          Performs a reverse k-nearest neighbor query for the given object ID.
 

Method parameters in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn with type arguments of type DistanceResultPair
private  void RdKNNTree.doReverseKNN(RdKNNNode<D,N> node, O o, List<DistanceResultPair<D>> result)
          Performs a reverse knn query in the specified subtree.
 

Uses of DistanceResultPair in de.lmu.ifi.dbs.elki.math.linearalgebra.pca
 

Method parameters in de.lmu.ifi.dbs.elki.math.linearalgebra.pca with type arguments of type DistanceResultPair
 PCAFilteredResult PCAFilteredRunner.processQueryResult(Collection<DistanceResultPair<D>> results, Database<V> database)
          Run PCA on a QueryResult Collection
 PCAResult PCARunner.processQueryResult(Collection<DistanceResultPair<D>> results, Database<V> database)
          Run PCA on a QueryResult Collection
 Matrix CovarianceMatrixBuilder.processQueryResults(Collection<DistanceResultPair<D>> results, Database<V> database)
          Compute Covariance Matrix for a QueryResult Collection By default it will just collect the ids and run processIds
 Matrix WeightedCovarianceMatrixBuilder.processQueryResults(Collection<DistanceResultPair<D>> results, Database<V> database, int k)
          Compute Covariance Matrix for a QueryResult Collection By default it will just collect the ids and run processIds
 Matrix CovarianceMatrixBuilder.processQueryResults(Collection<DistanceResultPair<D>> results, Database<V> database, int k)
          Compute Covariance Matrix for a QueryResult Collection By default it will just collect the ids and run processIds
 

Uses of DistanceResultPair in de.lmu.ifi.dbs.elki.preprocessing
 

Fields in de.lmu.ifi.dbs.elki.preprocessing with type parameters of type DistanceResultPair
protected  HashMap<Integer,List<DistanceResultPair<D>>> MaterializeKNNPreprocessor.materialized
          Materialized neighborhood
 

Methods in de.lmu.ifi.dbs.elki.preprocessing that return types with arguments of type DistanceResultPair
 HashMap<Integer,List<DistanceResultPair<D>>> MaterializeKNNPreprocessor.getMaterialized()
          Materialize a neighborhood.
protected  List<DistanceResultPair<DoubleDistance>> KnnQueryBasedHiCOPreprocessor.resultsForPCA(Integer id, Database<V> database, boolean verbose, boolean time)
           
protected  List<DistanceResultPair<DoubleDistance>> RangeQueryBasedHiCOPreprocessor.resultsForPCA(Integer id, Database<V> database, boolean verbose, boolean time)
           
protected abstract  List<DistanceResultPair<DoubleDistance>> HiCOPreprocessor.resultsForPCA(Integer id, Database<V> database, boolean verbose, boolean time)
          Returns the ids of the objects and distances stored in the specified database to be considered within the PCA for the specified object id.
 

Method parameters in de.lmu.ifi.dbs.elki.preprocessing with type arguments of type DistanceResultPair
protected  void FourCPreprocessor.runVarianceAnalysis(Integer id, List<DistanceResultPair<D>> neighbors, Database<V> database)
          This method implements the type of variance analysis to be computed for a given point.
protected abstract  void ProjectedDBSCANPreprocessor.runVarianceAnalysis(Integer id, List<DistanceResultPair<D>> neighbors, Database<V> database)
          This method implements the type of variance analysis to be computed for a given point.
protected  void PreDeConPreprocessor.runVarianceAnalysis(Integer id, List<DistanceResultPair<D>> neighbors, Database<V> database)
          TODO provide correct commentary This method implements the type of variance analysis to be computed for a given point.
 


Release 0.2.1 (2009-07-13_1605)