Uses of Interface
de.lmu.ifi.dbs.elki.database.query.knn.KNNQuery

Packages that use KNNQuery

Package	Description
de.lmu.ifi.dbs.elki.algorithm.classification	Classification algorithms.
de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan	Generalized DBSCAN Generalized DBSCAN is an abstraction of the original DBSCAN idea, that allows the use of arbitrary "neighborhood" and "core point" predicates.
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical	Hierarchical agglomerative clustering (HAC).
de.lmu.ifi.dbs.elki.algorithm.outlier	Outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic	Outlier detection algorithms based on intrinsic dimensionality.
de.lmu.ifi.dbs.elki.algorithm.outlier.lof	LOF family of outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.projection	Data projections (see also preprocessing filters for basic projections).
de.lmu.ifi.dbs.elki.algorithm.statistics	Statistical analysis algorithms.
de.lmu.ifi.dbs.elki.database	ELKI database layer - loading, storing, indexing and accessing data
de.lmu.ifi.dbs.elki.database.query.knn	Prepared queries for k nearest neighbor (kNN) queries
de.lmu.ifi.dbs.elki.database.query.rknn	Prepared queries for reverse k nearest neighbor (rkNN) queries
de.lmu.ifi.dbs.elki.database.relation	Relations, materialized and virtual (views)
de.lmu.ifi.dbs.elki.index	Index structure implementations
de.lmu.ifi.dbs.elki.index.distancematrix	Precomputed distance matrix.
de.lmu.ifi.dbs.elki.index.idistance	iDistance is a distance based indexing technique, using a reference points embedding.
de.lmu.ifi.dbs.elki.index.invertedlist	Indexes using inverted lists.
de.lmu.ifi.dbs.elki.index.lsh	Locality Sensitive Hashing
de.lmu.ifi.dbs.elki.index.preprocessed.knn	Indexes providing KNN and rKNN data.
de.lmu.ifi.dbs.elki.index.preprocessed.localpca	Index using a preprocessed local PCA
de.lmu.ifi.dbs.elki.index.projected	Projected indexes for data
de.lmu.ifi.dbs.elki.index.tree.metrical.covertree	Cover-tree variations.
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees	Metrical index structures based on the concepts of the M-Tree supporting processing of reverse k nearest neighbor queries by using the k-nn distances of the entries
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp	MkAppTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop	MkCoPTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax	MkMaxTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab	MkTabTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree	MTree
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.query	Classes for performing queries (knn, range, ...) on metrical trees
de.lmu.ifi.dbs.elki.index.tree.spatial.kd	K-d-tree and variants
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu	DeLiCluTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat	FlatRStarTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query	Queries on the R-Tree family of indexes: kNN and range queries
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn	RdKNNTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar	RStarTree
de.lmu.ifi.dbs.elki.index.vafile	Vector Approximation File
de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality	Methods for estimating the intrinsic dimensionality.
de.lmu.ifi.dbs.elki.parallel.processor	Processor API of ELKI, and some essential shared processors.

Uses of KNNQuery in de.lmu.ifi.dbs.elki.algorithm.classification

Fields in de.lmu.ifi.dbs.elki.algorithm.classification declared as KNNQuery

Modifier and Type	Field and Description
protected KNNQuery<O>	KNNClassifier.knnq kNN query class.

Uses of KNNQuery in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan with parameters of type KNNQuery

Modifier and Type	Method and Description
protected int	LSDBC.expandCluster(int clusterid, WritableIntegerDataStore clusterids, KNNQuery<O> knnq, DBIDs neighbors, double maxkdist, FiniteProgress progress) Set-based expand cluster implementation.
private void	LSDBC.fillDensities(KNNQuery<O> knnq, DBIDs ids, WritableDoubleDataStore dens) Collect all densities into an array for sorting.

Uses of KNNQuery in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical with parameters of type KNNQuery

Modifier and Type	Method and Description
protected WritableDoubleDataStore	AbstractHDBSCAN.computeCoreDists(DBIDs ids, KNNQuery<O> knnQ, int minPts) Compute the core distances for all objects.

Uses of KNNQuery in de.lmu.ifi.dbs.elki.algorithm.outlier

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier with parameters of type KNNQuery

Modifier and Type	Method and Description
private void	DWOF.initializeRadii(DBIDs ids, KNNQuery<O> knnq, DistanceQuery<O> distFunc, WritableDoubleDataStore radii) This method prepares a container for the radii of the objects and initializes radii according to the equation: initialRadii of a certain object = (absoluteMinDist of all objects) * (avgDist of the object) / (minAvgDist of all objects)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic with parameters of type KNNQuery

Modifier and Type	Method and Description
protected DoubleDataStore	IDOS.computeIDOS(DBIDs ids, KNNQuery<O> knnQ, DoubleDataStore intDims, DoubleMinMax idosminmax) Computes all IDOS scores.
protected DoubleDataStore	IDOS.computeIDs(DBIDs ids, KNNQuery<O> knnQ) Computes all IDs

Uses of KNNQuery in de.lmu.ifi.dbs.elki.algorithm.outlier.lof

Fields in de.lmu.ifi.dbs.elki.algorithm.outlier.lof declared as KNNQuery

Modifier and Type	Field and Description
private KNNQuery<O>	FlexibleLOF.LOFResult.kNNReach The kNN query w.r.t. the reachability distance.
private KNNQuery<O>	FlexibleLOF.LOFResult.kNNRefer The kNN query w.r.t. the reference neighborhood distance.

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.lof that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	FlexibleLOF.LOFResult.getKNNReach() Get the knn query for the reachability set.
KNNQuery<O>	FlexibleLOF.LOFResult.getKNNRefer() Get the knn query for the reference set.

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.lof that return types with arguments of type KNNQuery

Modifier and Type	Method and Description
private Pair<Pair<KNNQuery<O>,KNNQuery<O>>,Pair<RKNNQuery<O>,RKNNQuery<O>>>	OnlineLOF.getKNNAndRkNNQueries(Database database, Relation<O> relation, StepProgress stepprog) Get the kNN and rkNN queries for the algorithm.
private Pair<Pair<KNNQuery<O>,KNNQuery<O>>,Pair<RKNNQuery<O>,RKNNQuery<O>>>	OnlineLOF.getKNNAndRkNNQueries(Database database, Relation<O> relation, StepProgress stepprog) Get the kNN and rkNN queries for the algorithm.
private Pair<KNNQuery<O>,KNNQuery<O>>	FlexibleLOF.getKNNQueries(Database database, Relation<O> relation, StepProgress stepprog) Get the kNN queries for the algorithm.
private Pair<KNNQuery<O>,KNNQuery<O>>	FlexibleLOF.getKNNQueries(Database database, Relation<O> relation, StepProgress stepprog) Get the kNN queries for the algorithm.
protected Pair<KNNQuery<O>,KNNQuery<O>>	LoOP.getKNNQueries(Database database, Relation<O> relation, StepProgress stepprog) Get the kNN queries for the algorithm.
protected Pair<KNNQuery<O>,KNNQuery<O>>	LoOP.getKNNQueries(Database database, Relation<O> relation, StepProgress stepprog) Get the kNN queries for the algorithm.

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.lof with parameters of type KNNQuery

Modifier and Type	Method and Description
protected void	COF.computeAverageChainingDistances(KNNQuery<O> knnq, DistanceQuery<O> dq, DBIDs ids, WritableDoubleDataStore acds) Computes the average chaining distance, the average length of a path through the given set of points to each target.
private void	COF.computeCOFScores(KNNQuery<O> knnq, DBIDs ids, DoubleDataStore acds, WritableDoubleDataStore cofs, DoubleMinMax cofminmax) Compute Connectivity outlier factors.
protected void	INFLO.computeINFLO(Relation<O> relation, ModifiableDBIDs pruned, KNNQuery<O> knnq, WritableDataStore<ModifiableDBIDs> rNNminuskNNs, WritableDoubleDataStore inflos, DoubleMinMax inflominmax) Compute the final INFLO scores.
protected void	FlexibleLOF.computeLOFs(KNNQuery<O> knnq, DBIDs ids, DoubleDataStore lrds, WritableDoubleDataStore lofs, DoubleMinMax lofminmax) Computes the Local outlier factor (LOF) of the specified objects.
protected double	LOF.computeLOFScore(KNNQuery<O> knnq, DBIDRef cur, DoubleDataStore lrds) Compute a single LOF score.
private void	LOF.computeLOFScores(KNNQuery<O> knnq, DBIDs ids, DoubleDataStore lrds, WritableDoubleDataStore lofs, DoubleMinMax lofminmax) Compute local outlier factors.
protected double	LOF.computeLRD(KNNQuery<O> knnq, DBIDIter curr) Compute a single local reachability distance.
private void	LOF.computeLRDs(KNNQuery<O> knnq, DBIDs ids, WritableDoubleDataStore lrds) Compute local reachability distances.
protected void	FlexibleLOF.computeLRDs(KNNQuery<O> knnq, DBIDs ids, WritableDoubleDataStore lrds) Computes the local reachability density (LRD) of the specified objects.
protected void	KDEOS.computeOutlierScores(KNNQuery<O> knnq, DBIDs ids, WritableDataStore<double[]> densities, WritableDoubleDataStore kdeos, DoubleMinMax minmax) Compute the final KDEOS scores.
protected void	LoOP.computePDists(Relation<O> relation, KNNQuery<O> knn, WritableDoubleDataStore pdists) Compute the probabilistic distances used by LoOP.
protected double	LoOP.computePLOFs(Relation<O> relation, KNNQuery<O> knn, WritableDoubleDataStore pdists, WritableDoubleDataStore plofs) Compute the LOF values, using the pdist distances.
private void	SimplifiedLOF.computeSimplifiedLOFs(DBIDs ids, KNNQuery<O> knnq, WritableDoubleDataStore slrds, WritableDoubleDataStore lofs, DoubleMinMax lofminmax) Compute the simplified LOF factors.
private void	SimplifiedLOF.computeSimplifiedLRDs(DBIDs ids, KNNQuery<O> knnq, WritableDoubleDataStore lrds) Compute the simplified reachability densities.
private void	VarianceOfVolume.computeVolumes(KNNQuery<O> knnq, int dim, DBIDs ids, WritableDoubleDataStore vols) Compute volumes
private void	VarianceOfVolume.computeVOVs(KNNQuery<O> knnq, DBIDs ids, DoubleDataStore vols, WritableDoubleDataStore vovs, DoubleMinMax vovminmax) Compute variance of volumes.
protected FlexibleLOF.LOFResult<O>	FlexibleLOF.doRunInTime(DBIDs ids, KNNQuery<O> kNNRefer, KNNQuery<O> kNNReach, StepProgress stepprog) Performs the Generalized LOF_SCORE algorithm on the given database and returns a FlexibleLOF.LOFResult encapsulating information that may be needed by an OnlineLOF algorithm.
protected FlexibleLOF.LOFResult<O>	FlexibleLOF.doRunInTime(DBIDs ids, KNNQuery<O> kNNRefer, KNNQuery<O> kNNReach, StepProgress stepprog) Performs the Generalized LOF_SCORE algorithm on the given database and returns a FlexibleLOF.LOFResult encapsulating information that may be needed by an OnlineLOF algorithm.
protected void	KDEOS.estimateDensities(Relation<O> rel, KNNQuery<O> knnq, DBIDs ids, WritableDataStore<double[]> densities) Perform the kernel density estimation step.

Constructors in de.lmu.ifi.dbs.elki.algorithm.outlier.lof with parameters of type KNNQuery

Constructor and Description
LOFResult(OutlierResult result, KNNQuery<O> kNNRefer, KNNQuery<O> kNNReach, WritableDoubleDataStore lrds, WritableDoubleDataStore lofs) Encapsulates information generated during a run of the FlexibleLOF algorithm.
LOFResult(OutlierResult result, KNNQuery<O> kNNRefer, KNNQuery<O> kNNReach, WritableDoubleDataStore lrds, WritableDoubleDataStore lofs) Encapsulates information generated during a run of the FlexibleLOF algorithm.

Uses of KNNQuery in de.lmu.ifi.dbs.elki.algorithm.projection

Methods in de.lmu.ifi.dbs.elki.algorithm.projection with parameters of type KNNQuery

Modifier and Type	Method and Description
protected void	NearestNeighborAffinityMatrixBuilder.computePij(DBIDRange ids, KNNQuery<?> knnq, boolean square, int numberOfNeighbours, double[][] pij, int[][] indices, double initialScale) Compute the sparse pij using the nearest neighbors only.
protected void	IntrinsicNearestNeighborAffinityMatrixBuilder.computePij(DBIDRange ids, KNNQuery<?> knnq, boolean square, int numberOfNeighbours, double[][] pij, int[][] indices, double initialScale) Compute the sparse pij using the nearest neighbors only.

Uses of KNNQuery in de.lmu.ifi.dbs.elki.algorithm.statistics

Methods in de.lmu.ifi.dbs.elki.algorithm.statistics with parameters of type KNNQuery

Modifier and Type	Method and Description
protected double	HopkinsStatisticClusteringTendency.computeNNForRealData(KNNQuery<NumberVector> knnQuery, Relation<NumberVector> relation, int dim) Search nearest neighbors for real data members.
protected double	HopkinsStatisticClusteringTendency.computeNNForUniformData(KNNQuery<NumberVector> knnQuery, double[] min, double[] extend) Search nearest neighbors for artificial, uniform data.

Uses of KNNQuery in de.lmu.ifi.dbs.elki.database

Methods in de.lmu.ifi.dbs.elki.database that return KNNQuery

Modifier and Type	Method and Description
static <O> KNNQuery<O>	QueryUtil.getKNNQuery(Database database, DistanceFunction<? super O> distanceFunction, java.lang.Object... hints) Get a KNN query object for the given distance function.
<O> KNNQuery<O>	Database.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints) Get a KNN query object for the given distance query.
<O> KNNQuery<O>	AbstractDatabase.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
static <O> KNNQuery<O>	QueryUtil.getKNNQuery(Relation<O> relation, DistanceFunction<? super O> distanceFunction, java.lang.Object... hints) Get a KNN query object for the given distance function.
static <O> KNNQuery<O>	QueryUtil.getLinearScanKNNQuery(DistanceQuery<O> distanceQuery) Get a linear scan query for the given distance query.
static <O> KNNQuery<O>	DatabaseUtil.precomputedKNNQuery(Database database, Relation<O> relation, DistanceFunction<? super O> distf, int k) Get (or create) a precomputed kNN query for the database.
static <O> KNNQuery<O>	DatabaseUtil.precomputedKNNQuery(Database database, Relation<O> relation, DistanceQuery<O> dq, int k) Get (or create) a precomputed kNN query for the database.

Uses of KNNQuery in de.lmu.ifi.dbs.elki.database.query.knn

Classes in de.lmu.ifi.dbs.elki.database.query.knn that implement KNNQuery

Modifier and Type	Class and Description
class	AbstractDistanceKNNQuery<O> Instance for the query on a particular database.
class	LinearScanDistanceKNNQuery<O> Instance of this query for a particular database.
class	LinearScanEuclideanDistanceKNNQuery<O extends NumberVector> Instance of this query for a particular database.
class	LinearScanPrimitiveDistanceKNNQuery<O> Instance of this query for a particular database.
class	PreprocessorKNNQuery<O> Instance for a particular database, invoking the preprocessor.

Uses of KNNQuery in de.lmu.ifi.dbs.elki.database.query.rknn

Fields in de.lmu.ifi.dbs.elki.database.query.rknn declared as KNNQuery

Modifier and Type	Field and Description
protected KNNQuery<O>	LinearScanRKNNQuery.knnQuery KNN query we use.

Constructors in de.lmu.ifi.dbs.elki.database.query.rknn with parameters of type KNNQuery

Constructor and Description
LinearScanRKNNQuery(DistanceQuery<O> distanceQuery, KNNQuery<O> knnQuery, java.lang.Integer maxk) Constructor.

Uses of KNNQuery in de.lmu.ifi.dbs.elki.database.relation

Methods in de.lmu.ifi.dbs.elki.database.relation that return KNNQuery

Modifier and Type	Method and Description
default KNNQuery<O>	Relation.getKNNQuery(DistanceFunction<? super O> distanceFunction, java.lang.Object... hints) Get a KNN query object for the given distance query.
KNNQuery<O>	Relation.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints) Get a KNN query object for the given distance query.
KNNQuery<O>	AbstractRelation.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index

Classes in de.lmu.ifi.dbs.elki.index that implement KNNQuery

Modifier and Type	Class and Description
class	AbstractRefiningIndex.AbstractKNNQuery KNN query for this index.

Methods in de.lmu.ifi.dbs.elki.index that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	KNNIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints) Get a KNN query object for the given distance query and k.

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.distancematrix

Classes in de.lmu.ifi.dbs.elki.index.distancematrix that implement KNNQuery

Modifier and Type	Class and Description
private class	PrecomputedDistanceMatrix.PrecomputedKNNQuery kNN query using the distance matrix.

Methods in de.lmu.ifi.dbs.elki.index.distancematrix that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	PrecomputedDistanceMatrix.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.idistance

Classes in de.lmu.ifi.dbs.elki.index.idistance that implement KNNQuery

Modifier and Type	Class and Description
protected class	InMemoryIDistanceIndex.IDistanceKNNQuery kNN query implementation.

Methods in de.lmu.ifi.dbs.elki.index.idistance that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	InMemoryIDistanceIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.invertedlist

Classes in de.lmu.ifi.dbs.elki.index.invertedlist that implement KNNQuery

Modifier and Type	Class and Description
protected class	InMemoryInvertedIndex.ArcCosineKNNQuery kNN query object, for arc cosine distance.
protected class	InMemoryInvertedIndex.CosineKNNQuery kNN query object, for cosine distance.

Methods in de.lmu.ifi.dbs.elki.index.invertedlist that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<V>	InMemoryInvertedIndex.getKNNQuery(DistanceQuery<V> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.lsh

Classes in de.lmu.ifi.dbs.elki.index.lsh that implement KNNQuery

Modifier and Type	Class and Description
protected class	InMemoryLSHIndex.Instance.LSHKNNQuery Class for handling kNN queries against the LSH index.

Methods in de.lmu.ifi.dbs.elki.index.lsh that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<V>	InMemoryLSHIndex.Instance.getKNNQuery(DistanceQuery<V> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.preprocessed.knn

Classes in de.lmu.ifi.dbs.elki.index.preprocessed.knn that implement KNNQuery

Modifier and Type	Class and Description
protected class	NaiveProjectedKNNPreprocessor.NaiveProjectedKNNQuery KNN Query processor for naive projections.
protected class	SpacefillingKNNPreprocessor.SpaceFillingKNNQuery KNN Query processor for space filling curves

Fields in de.lmu.ifi.dbs.elki.index.preprocessed.knn declared as KNNQuery

Modifier and Type	Field and Description
protected KNNQuery<O>	MaterializeKNNPreprocessor.knnQuery KNNQuery instance to use.

Methods in de.lmu.ifi.dbs.elki.index.preprocessed.knn that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	NNDescent.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
KNNQuery<O>	NaiveProjectedKNNPreprocessor.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
KNNQuery<O>	SpacefillingMaterializeKNNPreprocessor.getKNNQuery(DistanceQuery<O> distQ, java.lang.Object... hints)
KNNQuery<O>	SpacefillingKNNPreprocessor.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
KNNQuery<O>	AbstractMaterializeKNNPreprocessor.getKNNQuery(DistanceQuery<O> distQ, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.preprocessed.localpca

Fields in de.lmu.ifi.dbs.elki.index.preprocessed.localpca declared as KNNQuery

Modifier and Type	Field and Description
private KNNQuery<NV>	KNNQueryFilteredPCAIndex.knnQuery The kNN query instance we use.

Constructors in de.lmu.ifi.dbs.elki.index.preprocessed.localpca with parameters of type KNNQuery

Constructor and Description
KNNQueryFilteredPCAIndex(Relation<NV> relation, PCARunner pca, EigenPairFilter filter, KNNQuery<NV> knnQuery, int k) Constructor.

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.projected

Classes in de.lmu.ifi.dbs.elki.index.projected that implement KNNQuery

Modifier and Type	Class and Description
(package private) class	ProjectedIndex.ProjectedKNNQuery Class to proxy kNN queries.

Fields in de.lmu.ifi.dbs.elki.index.projected declared as KNNQuery

Modifier and Type	Field and Description
(package private) KNNQuery<I>	ProjectedIndex.ProjectedKNNQuery.inner Inner kNN query.

Methods in de.lmu.ifi.dbs.elki.index.projected that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	LatLngAsECEFIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
KNNQuery<O>	LngLatAsECEFIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
KNNQuery<O>	ProjectedIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

Constructors in de.lmu.ifi.dbs.elki.index.projected with parameters of type KNNQuery

Constructor and Description
ProjectedKNNQuery(DistanceQuery<O> distanceQuery, KNNQuery<I> inner) Constructor.

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree

Classes in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree that implement KNNQuery

Modifier and Type	Class and Description
class	CoverTree.CoverTreeKNNQuery KNN Query class.
class	SimplifiedCoverTree.CoverTreeKNNQuery KNN Query class.

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.covertree that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	CoverTree.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
KNNQuery<O>	SimplifiedCoverTree.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees

Fields in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees declared as KNNQuery

Modifier and Type	Field and Description
protected KNNQuery<O>	AbstractMkTree.knnq Internal class for performing knn queries

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	MkAppTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	MkCoPTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	MkMaxTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	MkTabTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	MTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.query

Classes in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.query that implement KNNQuery

Modifier and Type	Class and Description
class	MTreeKNNQuery<O> Instance of a KNN query for a particular spatial index.

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.tree.spatial.kd

Classes in de.lmu.ifi.dbs.elki.index.tree.spatial.kd that implement KNNQuery

Modifier and Type	Class and Description
class	MinimalisticMemoryKDTree.KDTreeKNNQuery kNN query for the k-d-tree.
class	SmallMemoryKDTree.KDTreeKNNQuery kNN query for the k-d-tree.

Methods in de.lmu.ifi.dbs.elki.index.tree.spatial.kd that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	MinimalisticMemoryKDTree.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)
KNNQuery<O>	SmallMemoryKDTree.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu

Methods in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	DeLiCluTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat

Methods in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.flat that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	FlatRStarTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query

Classes in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query that implement KNNQuery

Modifier and Type	Class and Description
class	EuclideanRStarTreeKNNQuery<O extends NumberVector> Instance of a KNN query for a particular spatial index.
class	RStarTreeKNNQuery<O extends SpatialComparable> Instance of a KNN query for a particular spatial index.

Methods in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query that return KNNQuery

Modifier and Type	Method and Description
static <O extends SpatialComparable> KNNQuery<O>	RStarTreeUtil.getKNNQuery(AbstractRStarTree<?,?,?> tree, SpatialDistanceQuery<O> distanceQuery, java.lang.Object... hints) Get an RTree knn query, using an optimized double implementation when possible.

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn

Fields in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn declared as KNNQuery

Modifier and Type	Field and Description
protected KNNQuery<O>	RdKNNTree.knnQuery Internal knn query object, for updating the rKNN.

Methods in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	RdKNNTree.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

Methods in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn with parameters of type KNNQuery

Modifier and Type	Method and Description
java.util.List<ModifiableDoubleDBIDList>	RdKNNTree.bulkReverseKNNQueryForID(DBIDs ids, int k, SpatialPrimitiveDistanceFunction<? super O> distanceFunction, KNNQuery<O> knnQuery)
DoubleDBIDList	RdKNNTree.reverseKNNQuery(DBID oid, int k, SpatialPrimitiveDistanceFunction<? super O> distanceFunction, KNNQuery<O> knnQuery)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar

Methods in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<O>	RStarTreeIndex.getKNNQuery(DistanceQuery<O> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.index.vafile

Classes in de.lmu.ifi.dbs.elki.index.vafile that implement KNNQuery

Modifier and Type	Class and Description
class	PartialVAFile.PartialVAFileKNNQuery KNN query for this index.
class	VAFile.VAFileKNNQuery KNN query for this index.

Methods in de.lmu.ifi.dbs.elki.index.vafile that return KNNQuery

Modifier and Type	Method and Description
KNNQuery<V>	PartialVAFile.getKNNQuery(DistanceQuery<V> distanceQuery, java.lang.Object... hints)
KNNQuery<V>	VAFile.getKNNQuery(DistanceQuery<V> distanceQuery, java.lang.Object... hints)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality

Methods in de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality with parameters of type KNNQuery

Modifier and Type	Method and Description
default double	IntrinsicDimensionalityEstimator.estimate(KNNQuery<?> knnq, DBIDRef cur, int k) Estimate from a Reference Point, a KNNQuery and the neighborhood size k.
double	ALIDEstimator.estimate(KNNQuery<?> knnq, DBIDRef cur, int k)

Uses of KNNQuery in de.lmu.ifi.dbs.elki.parallel.processor

Fields in de.lmu.ifi.dbs.elki.parallel.processor declared as KNNQuery

Modifier and Type	Field and Description
(package private) KNNQuery<O>	KNNProcessor.knnq KNN query object
(package private) KNNQuery<O>	KNNProcessor.Instance.knnq kNN query

Constructors in de.lmu.ifi.dbs.elki.parallel.processor with parameters of type KNNQuery

Constructor and Description
Instance(int k, KNNQuery<O> knnq, SharedObject.Instance<KNNList> out) Constructor.
KNNProcessor(int k, KNNQuery<O> knnq) Constructor.