| Modifier and Type | Class and Description |
|---|---|
class |
AbstractRefiningIndex<O>
Abstract base class for Filter-refinement indexes.
|
| Modifier and Type | Class and Description |
|---|---|
class |
PrecomputedDistanceMatrix<O>
Distance matrix, for precomputing similarity for a small data set.
|
| Modifier and Type | Class and Description |
|---|---|
class |
InMemoryIDistanceIndex<O>
In-memory iDistance index, a metric indexing method using a reference point
embedding.
|
| Modifier and Type | Class and Description |
|---|---|
class |
InMemoryInvertedIndex<V extends NumberVector>
Simple index using inverted lists.
|
| Modifier and Type | Class and Description |
|---|---|
class |
InMemoryLSHIndex.Instance
Instance of a LSH index for a single relation.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractPreprocessorIndex<O,R>
Abstract base class for simple preprocessor based indexes, requiring a simple
object storage for preprocessing results.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractMaterializeKNNPreprocessor<O>
Abstract base class for KNN Preprocessors.
|
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 |
NaiveProjectedKNNPreprocessor<O extends NumberVector>
Compute the approximate k nearest neighbors using 1 dimensional projections.
|
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 |
SpacefillingKNNPreprocessor<O extends NumberVector>
Compute the nearest neighbors approximatively using space filling curves.
|
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 | Class and Description |
|---|---|
class |
AbstractFilteredPCAIndex<NV extends NumberVector>
Abstract base class for a local PCA based index.
|
class |
KNNQueryFilteredPCAIndex<NV extends NumberVector>
Provides the local neighborhood to be considered in the PCA as the k nearest
neighbors of an object.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractPreferenceVectorIndex<NV extends NumberVector>
Abstract base class for preference vector based algorithms.
|
class |
DiSHPreferenceVectorIndex<V extends NumberVector>
Preprocessor for DiSH preference vector assignment to objects of a certain
database.
|
class |
HiSCPreferenceVectorIndex<V extends NumberVector>
Preprocessor for HiSC preference vector assignment to objects of a certain
database.
|
| Modifier and Type | Class and Description |
|---|---|
class |
SharedNearestNeighborPreprocessor<O>
A preprocessor for annotation of the ids of nearest neighbors to each
database object.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractCoverTree<O>
Abstract base class for cover tree variants.
|
class |
CoverTree<O>
Cover tree data structure (in-memory).
|
class |
SimplifiedCoverTree<O>
Simplified cover tree data structure (in-memory).
|
| Modifier and Type | Class and Description |
|---|---|
class |
MinimalisticMemoryKDTree<O extends NumberVector>
Simple implementation of a static in-memory K-D-tree.
|
class |
SmallMemoryKDTree<O extends NumberVector>
Simple implementation of a static in-memory K-D-tree.
|
| Modifier and Type | Class and Description |
|---|---|
class |
PartialVAFile<V extends NumberVector>
PartialVAFile.
|
class |
VAFile<V extends NumberVector>
Vector-approximation file (VAFile)
Reference:
Weber, R. and Blott, S.
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.