Uses of Class
elki.index.preprocessed.knn.AbstractMaterializeKNNPreprocessor

Packages that use AbstractMaterializeKNNPreprocessor

Package	Description
elki.database.query.knn	Prepared queries for k nearest neighbor (kNN) queries.
elki.index.preprocessed.knn	Indexes providing KNN and rKNN data.
elki.visualization.visualizers.scatterplot.selection	Visualizers for object selection based on 2D projections.

Uses of AbstractMaterializeKNNPreprocessor in elki.database.query.knn

Fields in elki.database.query.knn declared as AbstractMaterializeKNNPreprocessor

Modifier and Type	Field	Description
private AbstractMaterializeKNNPreprocessor<?>	PreprocessorKNNQuery.preprocessor	The last preprocessor result

Methods in elki.database.query.knn that return AbstractMaterializeKNNPreprocessor

Modifier and Type	Method	Description
AbstractMaterializeKNNPreprocessor<?>	PreprocessorKNNQuery.getPreprocessor()	Get the preprocessor instance.

Constructors in elki.database.query.knn with parameters of type AbstractMaterializeKNNPreprocessor

Constructor	Description
PreprocessorKNNQuery(Relation<?> relation, AbstractMaterializeKNNPreprocessor<?> preprocessor)	Constructor.
PreprocessorSqrtKNNQuery(Relation<?> relation, AbstractMaterializeKNNPreprocessor<?> preprocessor)	Constructor.
PreprocessorSquaredKNNQuery(Relation<?> relation, AbstractMaterializeKNNPreprocessor<?> preprocessor)	Constructor.

Uses of AbstractMaterializeKNNPreprocessor in elki.index.preprocessed.knn

Subclasses of AbstractMaterializeKNNPreprocessor in elki.index.preprocessed.knn

Modifier and Type	Class	Description
class	CachedDoubleDistanceKNNPreprocessor<O>	Preprocessor that loads an existing cached kNN result.
class	KNNJoinMaterializeKNNPreprocessor<V extends SpatialComparable>	Class to materialize the kNN using a spatial join on an R-tree.
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.
class	MaterializeKNNPreprocessor<O>	A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
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.
class	NNDescent<O>	NN-descent (also known as KNNGraph) is an approximate nearest neighbor search algorithm beginning with a random sample, then iteratively refining this sample until.
class	PartitionApproximationMaterializeKNNPreprocessor<O>	A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
class	RandomSampleKNNPreprocessor<O>	Class that computed the kNN only on a random sample.
class	SpacefillingMaterializeKNNPreprocessor<O extends NumberVector>	Compute the nearest neighbors approximatively using space filling curves.
class	SpatialApproximationMaterializeKNNPreprocessor<O extends NumberVector>	A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.

Methods in elki.index.preprocessed.knn that return AbstractMaterializeKNNPreprocessor

Modifier and Type	Method	Description
abstract AbstractMaterializeKNNPreprocessor<O>	AbstractMaterializeKNNPreprocessor.Factory.instantiate(Relation<O> relation)

Uses of AbstractMaterializeKNNPreprocessor in elki.visualization.visualizers.scatterplot.selection

Fields in elki.visualization.visualizers.scatterplot.selection declared as AbstractMaterializeKNNPreprocessor

Modifier and Type	Field	Description
private AbstractMaterializeKNNPreprocessor<? extends NumberVector>	DistanceFunctionVisualization.Instance.result	The selection result we work on

Methods in elki.visualization.visualizers.scatterplot.selection with parameters of type AbstractMaterializeKNNPreprocessor

Modifier and Type	Method	Description
static double	DistanceFunctionVisualization.getLPNormP(AbstractMaterializeKNNPreprocessor<?> kNN)	Get the "p" value of an Lp norm.
static boolean	DistanceFunctionVisualization.isAngularDistance(AbstractMaterializeKNNPreprocessor<?> kNN)	Test whether the given preprocessor used an angular distance function