Uses of Class
de.lmu.ifi.dbs.elki.utilities.datastructures.heap.KNNList

Packages that use KNNList

de.lmu.ifi.dbs.elki.algorithm	Algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.clustering	Clustering algorithms Clustering algorithms are supposed to implement the Algorithm-Interface.
de.lmu.ifi.dbs.elki.algorithm.outlier	Outlier detection algorithms
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.utilities.datastructures.heap	Heap structures and variations such as bounded priority heaps.

Uses of KNNList in de.lmu.ifi.dbs.elki.algorithm

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

DataStore<KNNList<D>>

KNNJoin.run(Database database, Relation<V> relation) Joins in the given spatial database to each object its k-nearest neighbors.

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

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

private void	DeLiClu.expandLeafNodes(SpatialPrimitiveDistanceFunction<NV,D> distFunction, DeLiCluNode node1, DeLiCluNode node2, DataStore<KNNList<D>> knns) Expands the specified leaf nodes.
private void	DeLiClu.expandNodes(DeLiCluTree index, SpatialPrimitiveDistanceFunction<NV,D> distFunction, DeLiClu.SpatialObjectPair nodePair, DataStore<KNNList<D>> knns) Expands the spatial nodes of the specified pair.
private void	DeLiClu.reinsertExpanded(SpatialPrimitiveDistanceFunction<NV,D> distFunction, DeLiCluTree index, List<TreeIndexPathComponent<DeLiCluEntry>> path, DataStore<KNNList<D>> knns) Reinserts the objects of the already expanded nodes.
private void	DeLiClu.reinsertExpanded(SpatialPrimitiveDistanceFunction<NV,D> distFunction, DeLiCluTree index, List<TreeIndexPathComponent<DeLiCluEntry>> path, int pos, SpatialDirectoryEntry parentEntry, DataStore<KNNList<D>> knns)

Uses of KNNList in de.lmu.ifi.dbs.elki.algorithm.outlier

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier that return KNNList

private KNNList<DoubleDistance>

SOD.getKNN(Relation<V> database, SimilarityQuery<V,IntegerDistance> snnInstance, DBID queryObject) Provides the k nearest neighbors in terms of the shared nearest neighbor distance.

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

Method parameters in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp with type arguments of type KNNList

private void	MkAppTree.adjustApproximatedKNNDistances(MkAppEntry<D> entry, Map<DBID,KNNList<D>> knnLists) Adjusts the knn distance in the subtree of the specified root entry.
private List<D>	MkAppTree.getMeanKNNList(DBIDs ids, Map<DBID,KNNList<D>> knnLists)

Uses of KNNList 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 with parameters of type KNNList

private void

MkCoPTree.approximateKnnDistances(MkCoPLeafEntry<D> entry, KNNList<D> knnDistances) Computes logarithmic skew (fractal dimension ie. m) and in kappx[0] and kappx[1] the non-logarithmic values of the approximated first and last nearest neighbor distances

Method parameters in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop with type arguments of type KNNList

private void

MkCoPTree.adjustApproximatedKNNDistances(MkCoPEntry<D> entry, Map<DBID,KNNList<D>> knnLists) Adjusts the knn distance in the subtree of the specified root entry.

Uses of KNNList in de.lmu.ifi.dbs.elki.utilities.datastructures.heap

Methods in de.lmu.ifi.dbs.elki.utilities.datastructures.heap that return KNNList

KNNList<D>

KNNHeap.toKNNList() Serialize to a KNNList.