Package de.lmu.ifi.dbs.elki.index.preprocessed.knn

Indexes providing KNN and rKNN data.

See: Description

Interface Summary

Interface	Description
KNNListener	Listener interface invoked when the k nearest neighbors (kNNs) of some objects have been changed due to insertion or removals of objects.

Class Summary

Class	Description
AbstractMaterializeKNNPreprocessor<O>	Abstract base class for KNN Preprocessors.
AbstractMaterializeKNNPreprocessor.Factory<O>	The parameterizable factory.
AbstractMaterializeKNNPreprocessor.Factory.Parameterizer<O>	Parameterization class.
CachedDoubleDistanceKNNPreprocessor<O>	Preprocessor that loads an existing cached kNN result.
CachedDoubleDistanceKNNPreprocessor.Factory<O>	The parameterizable factory.
CachedDoubleDistanceKNNPreprocessor.Factory.Parameterizer<O>	Parameterization class.
KNNChangeEvent	Encapsulates information describing changes of the k nearest neighbors (kNNs) of some objects due to insertion or removal of objects.
KNNJoinMaterializeKNNPreprocessor<V extends NumberVector>	Class to materialize the kNN using a spatial join on an R-tree.
KNNJoinMaterializeKNNPreprocessor.Factory<O extends NumberVector>	The parameterizable factory.
KNNJoinMaterializeKNNPreprocessor.Factory.Parameterizer<O extends NumberVector>	Parameterization class
MaterializeKNNAndRKNNPreprocessor<O>	A preprocessor for annotation of the k nearest neighbors and the reverse k nearest neighbors (and their distances) to each database object.
MaterializeKNNAndRKNNPreprocessor.Factory<O>	The parameterizable factory.
MaterializeKNNAndRKNNPreprocessor.Factory.Parameterizer<O>	Parameterization class.
MaterializeKNNPreprocessor<O>	A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
MaterializeKNNPreprocessor.Factory<O>	The parameterizable factory.
MaterializeKNNPreprocessor.Factory.Parameterizer<O>	Parameterization class.
MetricalIndexApproximationMaterializeKNNPreprocessor<O extends NumberVector,N extends Node<E>,E extends MTreeEntry>	A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
MetricalIndexApproximationMaterializeKNNPreprocessor.Factory<O extends NumberVector,N extends Node<E>,E extends MTreeEntry>	The parameterizable factory.
MetricalIndexApproximationMaterializeKNNPreprocessor.Factory.Parameterizer<O extends NumberVector,N extends Node<E>,E extends MTreeEntry>	Parameterization class.
NaiveProjectedKNNPreprocessor<O extends NumberVector>	Compute the approximate k nearest neighbors using 1 dimensional projections.
NaiveProjectedKNNPreprocessor.Factory<V extends NumberVector>	Index factory class
NaiveProjectedKNNPreprocessor.Factory.Parameterizer	Parameterization class.
NNDescent<O>	NN-desent (also known as KNNGraph) is an approximate nearest neighbor search algorithm beginning with a random sample, then iteratively refining this sample until.
NNDescent.Factory<O>	Index factory.
NNDescent.Factory.Parameterizer<O>	Parameterization class
PartitionApproximationMaterializeKNNPreprocessor<O>	A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
PartitionApproximationMaterializeKNNPreprocessor.Factory<O>	The parameterizable factory.
PartitionApproximationMaterializeKNNPreprocessor.Factory.Parameterizer<O>	Parameterization class.
RandomSampleKNNPreprocessor<O>	Class that computed the kNN only on a random sample.
RandomSampleKNNPreprocessor.Factory<O>	The parameterizable factory.
RandomSampleKNNPreprocessor.Factory.Parameterizer<O>	Parameterization class
SpacefillingKNNPreprocessor<O extends NumberVector>	Compute the nearest neighbors approximatively using space filling curves.
SpacefillingKNNPreprocessor.Factory<V extends NumberVector>	Index factory class
SpacefillingKNNPreprocessor.Factory.Parameterizer	Parameterization class.
SpacefillingMaterializeKNNPreprocessor<O extends NumberVector>	Compute the nearest neighbors approximatively using space filling curves.
SpacefillingMaterializeKNNPreprocessor.Factory<V extends NumberVector>	Index factory class
SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer<V extends NumberVector>	Parameterization class.
SpatialApproximationMaterializeKNNPreprocessor<O extends NumberVector,N extends SpatialNode<N,E>,E extends SpatialEntry>	A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
SpatialApproximationMaterializeKNNPreprocessor.Factory<N extends SpatialNode<N,E>,E extends SpatialEntry>	The actual preprocessor instance.
SpatialApproximationMaterializeKNNPreprocessor.Factory.Parameterizer<N extends SpatialNode<N,E>,E extends SpatialEntry>	Parameterization class.
SpatialPair<K,V extends SpatialComparable>	Defines the requirements for objects that can be indexed by a Spatial Index, which are spatial nodes or data objects.

Enum Summary

Enum	Description
KNNChangeEvent.Type	Available event types.

Package de.lmu.ifi.dbs.elki.index.preprocessed.knn Description

Indexes providing KNN and rKNN data.