Package | Description |
---|---|
de.lmu.ifi.dbs.elki.database.query.knn |
Prepared queries for k nearest neighbor (kNN) queries.
|
de.lmu.ifi.dbs.elki.index.preprocessed.knn |
Indexes providing KNN and rKNN data.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection |
Visualizers for object selection based on 2D projections.
|
Modifier and Type | Field and Description |
---|---|
private AbstractMaterializeKNNPreprocessor<O> |
PreprocessorKNNQuery.preprocessor
The last preprocessor result
|
Modifier and Type | Method and Description |
---|---|
AbstractMaterializeKNNPreprocessor<O> |
PreprocessorKNNQuery.getPreprocessor()
Get the preprocessor instance.
|
Constructor and Description |
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PreprocessorKNNQuery(Relation<O> relation,
AbstractMaterializeKNNPreprocessor<O> preprocessor)
Constructor.
|
Modifier and Type | Class and Description |
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class |
CachedDoubleDistanceKNNPreprocessor<O>
Preprocessor that loads an existing cached kNN result.
|
class |
KNNJoinMaterializeKNNPreprocessor<V extends NumberVector>
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 |
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,N extends SpatialNode<N,E>,E extends SpatialEntry>
A preprocessor for annotation of the k nearest neighbors (and their
distances) to each database object.
|
Modifier and Type | Method and Description |
---|---|
abstract AbstractMaterializeKNNPreprocessor<O> |
AbstractMaterializeKNNPreprocessor.Factory.instantiate(Relation<O> relation) |
Modifier and Type | Field and Description |
---|---|
private AbstractMaterializeKNNPreprocessor<? extends NumberVector> |
DistanceFunctionVisualization.Instance.result
The selection result we work on
|
Modifier and Type | Method and 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
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.