Modifier and Type | Class and Description |
---|---|
static class |
AbstractIndexBasedDistanceFunction.Instance<O,I extends Index,F extends DistanceFunction<? super O>>
The actual instance bound to a particular database.
|
static interface |
IndexBasedDistanceFunction.Instance<T,I extends Index>
Instance interface for Index based distance functions.
|
Modifier and Type | Field and Description |
---|---|
protected I |
AbstractIndexBasedDistanceFunction.Instance.index
Index we use
|
Modifier and Type | Class and Description |
---|---|
static class |
AbstractIndexBasedSimilarityFunction.Instance<O,I extends Index>
The actual instance bound to a particular database.
|
static interface |
IndexBasedSimilarityFunction.Instance<T,I extends Index>
Instance interface for index/preprocessor based distance functions.
|
Modifier and Type | Field and Description |
---|---|
protected I |
AbstractIndexBasedSimilarityFunction.Instance.index
Parent index
|
Modifier and Type | Interface and Description |
---|---|
interface |
DistanceIndex<O>
Index with support for distance queries (e.g. precomputed distance matrixes,
caches)
|
interface |
DynamicIndex
Index that supports dynamic insertions and removals.
|
interface |
KNNIndex<O>
Index with support for kNN queries.
|
interface |
RangeIndex<O>
Index with support for range queries (radius queries).
|
interface |
RKNNIndex<O>
Index with support for kNN queries.
|
interface |
SimilarityIndex<O>
Index with support for similarity queries (e.g. precomputed similarity
matrixes, caches)
|
interface |
SimilarityRangeIndex<O>
Index with support for similarity range queries.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractIndex<O>
Abstract base class for indexes with some implementation defaults.
|
class |
AbstractRefiningIndex<O>
Abstract base class for Filter-refinement indexes.
|
Modifier and Type | Method and Description |
---|---|
Index |
IndexFactory.instantiate(Relation<V> relation)
Sets the database in the distance function of this index (if existing).
|
Modifier and Type | Class and Description |
---|---|
class |
PrecomputedDistanceMatrix<O>
Distance matrix, for precomputing similarity for a small data set.
|
class |
PrecomputedSimilarityMatrix<O>
Precomputed similarity matrix, 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, for cosine distance only.
|
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 |
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.
|
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 | Interface and Description |
---|---|
interface |
FilteredLocalPCAIndex<NV extends NumberVector>
Interface for an index providing local PCA results.
|
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 | Interface and Description |
---|---|
interface |
PreferenceVectorIndex<NV extends NumberVector>
Interface for an index providing preference vectors.
|
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 | Interface and Description |
---|---|
interface |
SharedNearestNeighborIndex<O>
Interface for an index providing nearest neighbor sets.
|
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 |
LatLngAsECEFIndex<O extends NumberVector>
Index a 2d data set (consisting of Lat/Lng pairs) by using a projection to 3D
coordinates (WGS-86 to ECEF).
|
class |
LngLatAsECEFIndex<O extends NumberVector>
Index a 2d data set (consisting of Lng/Lat pairs) by using a projection to 3D
coordinates (WGS-86 to ECEF).
|
class |
ProjectedIndex<O,I>
Class to index data in an arbitrary projection only.
|
Modifier and Type | Field and Description |
---|---|
(package private) Index |
ProjectedIndex.inner
Inner index.
|
Constructor and Description |
---|
LatLngAsECEFIndex(Relation<? extends O> relation,
Projection<O,O> proj,
Relation<O> view,
Index inner,
boolean norefine)
Constructor.
|
LngLatAsECEFIndex(Relation<? extends O> relation,
Projection<O,O> proj,
Relation<O> view,
Index inner,
boolean norefine)
Constructor.
|
ProjectedIndex(Relation<? extends O> relation,
Projection<O,I> proj,
Relation<I> view,
Index inner,
boolean norefine,
double kmulti)
Constructor.
|
Modifier and Type | Class and Description |
---|---|
class |
IndexTree<N extends Node<E>,E extends Entry>
Abstract super class for all tree based index classes.
|
Modifier and Type | Class and Description |
---|---|
class |
MetricalIndexTree<O,N extends Node<E>,E extends Entry>
Abstract super class for all metrical index classes.
|
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 |
AbstractMTree<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry,S extends MTreeSettings<O,N,E>>
Abstract super class for all M-Tree variants.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractMkTree<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry,S extends MTreeSettings<O,N,E>>
Abstract class for all M-Tree variants supporting processing of reverse
k-nearest neighbor queries by using the k-nn distances of the entries, where
k is less than or equal to the given parameter.
|
class |
AbstractMkTreeUnified<O,N extends AbstractMTreeNode<O,N,E>,E extends MTreeEntry,S extends MkTreeSettings<O,N,E>>
Abstract class for all M-Tree variants supporting processing of reverse
k-nearest neighbor queries by using the k-nn distances of the entries, where
k is less than or equal to the given parameter.
|
Modifier and Type | Class and Description |
---|---|
class |
MkAppTree<O>
MkAppTree is a metrical index structure based on the concepts of the M-Tree
supporting efficient processing of reverse k nearest neighbor queries for
parameter k < kmax.
|
class |
MkAppTreeIndex<O>
MkAppTree used as database index.
|
Modifier and Type | Class and Description |
---|---|
class |
MkCoPTree<O>
MkCopTree is a metrical index structure based on the concepts of the M-Tree
supporting efficient processing of reverse k nearest neighbor queries for
parameter k < kmax.
|
class |
MkCoPTreeIndex<O>
MkCoPTree used as database index.
|
Modifier and Type | Class and Description |
---|---|
class |
MkMaxTree<O>
MkMaxTree is a metrical index structure based on the concepts of the M-Tree
supporting efficient processing of reverse k nearest neighbor queries for
parameter k <= k_max.
|
class |
MkMaxTreeIndex<O>
MkMax tree
|
Modifier and Type | Class and Description |
---|---|
class |
MkTabTree<O>
MkTabTree is a metrical index structure based on the concepts of the M-Tree
supporting efficient processing of reverse k nearest neighbor queries for
parameter k < kmax.
|
class |
MkTabTreeIndex<O>
MkTabTree used as database index.
|
Modifier and Type | Class and Description |
---|---|
class |
MTree<O>
MTree is a metrical index structure based on the concepts of the M-Tree.
|
class |
MTreeIndex<O>
Class for using an m-tree as database index.
|
Modifier and Type | Class and Description |
---|---|
class |
SpatialIndexTree<N extends SpatialNode<N,E>,E extends SpatialEntry>
Abstract super class for all spatial index tree classes.
|
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 |
AbstractRStarTree<N extends AbstractRStarTreeNode<N,E>,E extends SpatialEntry,S extends RTreeSettings>
Abstract superclass for index structures based on a R*-Tree.
|
class |
NonFlatRStarTree<N extends AbstractRStarTreeNode<N,E>,E extends SpatialEntry,S extends RTreeSettings>
Abstract superclass for all non-flat R*-Tree variants.
|
Modifier and Type | Class and Description |
---|---|
class |
DeLiCluTree
DeLiCluTree is a spatial index structure based on an R-Tree.
|
class |
DeLiCluTreeIndex<O extends NumberVector>
The common use of the DeLiClu tree: indexing number vectors.
|
Modifier and Type | Class and Description |
---|---|
class |
FlatRStarTree
FlatRTree is a spatial index structure based on a R*-Tree but with a flat
directory.
|
class |
FlatRStarTreeIndex<O extends NumberVector>
The common use of the flat rstar tree: indexing number vectors.
|
Modifier and Type | Class and Description |
---|---|
class |
RdKNNTree<O extends NumberVector>
RDkNNTree is a spatial index structure based on the concepts of the R*-Tree
supporting efficient processing of reverse k nearest neighbor queries.
|
Modifier and Type | Class and Description |
---|---|
class |
RStarTree
RStarTree is a spatial index structure based on the concepts of the R*-Tree.
|
class |
RStarTreeIndex<O extends NumberVector>
The common use of the rstar tree: indexing number vectors.
|
Modifier and Type | Class and Description |
---|---|
class |
PartialVAFile<V extends NumberVector>
PartialVAFile.
|
class |
VAFile<V extends NumberVector>
Vector-approximation file (VAFile)
Reference:
R.
|
Copyright © 2019 ELKI Development Team. License information.