Uses of Interface
de.lmu.ifi.dbs.elki.distance.distancevalue.Distance

Packages that use Distance

Package	Description
de.lmu.ifi.dbs.elki.algorithm	Algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.benchmark	Benchmarking pseudo algorithms.
de.lmu.ifi.dbs.elki.algorithm.clustering	Clustering algorithms.
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation	Correlation clustering algorithms
de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan	Generalized DBSCAN.
de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans	K-means clustering and variations.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality	Quality measures for k-Means results.
de.lmu.ifi.dbs.elki.algorithm.outlier	Outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood	Spatial outlier neighborhood classes
de.lmu.ifi.dbs.elki.data.model	Cluster models classes for various algorithms.
de.lmu.ifi.dbs.elki.database	ELKI database layer - loading, storing, indexing and accessing data
de.lmu.ifi.dbs.elki.database.ids	Database object identification and ID group handling API.
de.lmu.ifi.dbs.elki.database.ids.distance	Distance-DBID pairs, lists and heaps.
de.lmu.ifi.dbs.elki.database.ids.generic	Database object identification and ID group handling - generic implementations.
de.lmu.ifi.dbs.elki.database.ids.integer	Integer-based DBID implementation -- do not use directly - always use DBIDUtil.
de.lmu.ifi.dbs.elki.database.query	Database queries - computing distances, neighbors, similarities - API and general documentation.
de.lmu.ifi.dbs.elki.database.query.distance	Prepared queries for distances.
de.lmu.ifi.dbs.elki.database.query.knn	Prepared queries for k nearest neighbor (kNN) queries.
de.lmu.ifi.dbs.elki.database.query.range	Prepared queries for ε-range queries.
de.lmu.ifi.dbs.elki.database.query.rknn	Prepared queries for reverse k nearest neighbor (rkNN) queries.
de.lmu.ifi.dbs.elki.database.query.similarity	Prepared queries for similarity functions.
de.lmu.ifi.dbs.elki.distance	Distance values, distance functions and similarity functions.
de.lmu.ifi.dbs.elki.distance.distancefunction	Distance functions for use within ELKI.
de.lmu.ifi.dbs.elki.distance.distancefunction.external	Distance functions using external data sources.
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace	Distance functions based on subspaces.
de.lmu.ifi.dbs.elki.distance.distancevalue	Distance values, i.e. object storing an actual distance value along with comparison functions and value parsers.
de.lmu.ifi.dbs.elki.distance.similarityfunction	Similarity functions.
de.lmu.ifi.dbs.elki.evaluation.roc	Evaluation of rankings using ROC AUC (Receiver Operation Characteristics - Area Under Curve)
de.lmu.ifi.dbs.elki.index	Index structure implementations
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.snn	Indexes providing nearest neighbor sets
de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj	Index using a preprocessed local subspaces.
de.lmu.ifi.dbs.elki.index.projected	Projected indexes for data.
de.lmu.ifi.dbs.elki.index.tree.metrical	Tree-based index structures for metrical vector spaces.
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.query	Classes related to generic tree queries.
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.query	Queries on the R-Tree family of indexes: kNN and range queries.
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.result	Result types, representation and handling
de.lmu.ifi.dbs.elki.result.optics	Result classes for OPTICS.
de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters	Classes for various typed parameters.
de.lmu.ifi.dbs.elki.visualization.opticsplot	Code for drawing OPTICS plots
de.lmu.ifi.dbs.elki.visualization.projections	Visualization projections
de.lmu.ifi.dbs.elki.visualization.projector	Projectors are responsible for finding appropriate projections for data relations.
de.lmu.ifi.dbs.elki.visualization.visualizers.optics	Visualizers that do work on OPTICS plots
tutorial.outlier

Uses of Distance in de.lmu.ifi.dbs.elki.algorithm

Classes in de.lmu.ifi.dbs.elki.algorithm with type parameters of type Distance

Modifier and Type	Class and Description
class	AbstractDistanceBasedAlgorithm<O,D extends Distance<D>,R extends Result> Provides an abstract algorithm already setting the distance function.
static class	AbstractDistanceBasedAlgorithm.Parameterizer<O,D extends Distance<D>> Parameterization helper class.
class	AbstractPrimitiveDistanceBasedAlgorithm<O,D extends Distance<?>,R extends Result> Provides an abstract algorithm already setting the distance function.
static class	AbstractPrimitiveDistanceBasedAlgorithm.Parameterizer<O,D extends Distance<D>> Parameterization helper class.
class	DependencyDerivator<V extends NumberVector<?>,D extends Distance<D>> Dependency derivator computes quantitatively linear dependencies among attributes of a given dataset based on a linear correlation PCA.
static class	DependencyDerivator.Parameterizer<V extends NumberVector<?>,D extends Distance<D>> Parameterization class.
interface	DistanceBasedAlgorithm<O,D extends Distance<?>> Very broad interface for distance based algorithms.
class	KNNDistanceOrder<O,D extends Distance<D>> Provides an order of the kNN-distances for all objects within the database.
static class	KNNDistanceOrder.Parameterizer<O,D extends Distance<D>> Parameterization class.
class	KNNJoin<V extends NumberVector<?>,D extends Distance<D>,N extends SpatialNode<N,E>,E extends SpatialEntry> Joins in a given spatial database to each object its k-nearest neighbors.
static class	KNNJoin.Parameterizer<V extends NumberVector<?>,D extends Distance<D>,N extends SpatialNode<N,E>,E extends SpatialEntry> Parameterization class.

Fields in de.lmu.ifi.dbs.elki.algorithm declared as Distance

Modifier and Type	Field and Description
(package private) D	KNNJoin.Task.mindist Minimum distance.

Uses of Distance in de.lmu.ifi.dbs.elki.algorithm.benchmark

Classes in de.lmu.ifi.dbs.elki.algorithm.benchmark with type parameters of type Distance

Modifier and Type	Class and Description
class	KNNBenchmarkAlgorithm<O,D extends Distance<D>> Benchmarking algorithm that computes the k nearest neighbors for each query point.
static class	KNNBenchmarkAlgorithm.Parameterizer<O,D extends Distance<D>> Parameterization class
class	ValidateApproximativeKNNIndex<O,D extends Distance<D>> Algorithm to validate the quality of an approximative kNN index, by performing a number of queries and comparing them to the results obtained by exact indexing (e.g. linear scanning).
static class	ValidateApproximativeKNNIndex.Parameterizer<O,D extends Distance<D>> Parameterization class

Uses of Distance in de.lmu.ifi.dbs.elki.algorithm.clustering

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering with type parameters of type Distance

Modifier and Type	Class and Description
static class	AbstractProjectedDBSCAN.Parameterizer<V extends NumberVector<?>,D extends Distance<D>> Parameterization class.
class	CanopyPreClustering<O,D extends Distance<D>> Canopy pre-clustering is a simple preprocessing step for clustering.
static class	CanopyPreClustering.Parameterizer<O,D extends Distance<D>> Parameterization class
class	DBSCAN<O,D extends Distance<D>> DBSCAN provides the DBSCAN algorithm, an algorithm to find density-connected sets in a database.
static class	DBSCAN.Parameterizer<O,D extends Distance<D>> Parameterization class.
class	DeLiClu<NV extends NumberVector<?>,D extends Distance<D>> DeLiClu provides the DeLiClu algorithm, a hierarchical algorithm to find density-connected sets in a database.
static class	DeLiClu.Parameterizer<NV extends NumberVector<?>,D extends Distance<D>> Parameterization class.
class	OPTICS<O,D extends Distance<D>> OPTICS provides the OPTICS algorithm.
static class	OPTICS.Parameterizer<O,D extends Distance<D>> Parameterization class.
interface	OPTICSTypeAlgorithm<D extends Distance<D>> Interface for OPTICS type algorithms, that can be analysed by OPTICS Xi etc.

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering declared as Distance

Modifier and Type	Field and Description
(package private) D	DeLiClu.SpatialObjectPair.distance The current distance.
private D	OPTICS.epsilon Hold the value of OPTICS.EPSILON_ID.
protected D	OPTICS.Parameterizer.epsilon
protected D	DBSCAN.epsilon Holds the epsilon radius threshold.
protected D	DBSCAN.Parameterizer.epsilon
protected D	AbstractProjectedDBSCAN.Parameterizer.epsilon
private D	CanopyPreClustering.t1 Threshold for inclusion
private D	CanopyPreClustering.Parameterizer.t1 Threshold for inclusion
private D	CanopyPreClustering.t2 Threshold for removal
private D	CanopyPreClustering.Parameterizer.t2 Threshold for removal

Uses of Distance in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with type parameters of type Distance

Modifier and Type	Class and Description
class	COPAC<V extends NumberVector<?>,D extends Distance<D>> Provides the COPAC algorithm, an algorithm to partition a database according to the correlation dimension of its objects and to then perform an arbitrary clustering algorithm over the partitions.
static class	COPAC.Parameterizer<V extends NumberVector<?>,D extends Distance<D>> Parameterization class.

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

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan with type parameters of type Distance

Modifier and Type	Class and Description
class	EpsilonNeighborPredicate<O,D extends Distance<D>> The default DBSCAN and OPTICS neighbor predicate, using an epsilon-neighborhood.
static class	EpsilonNeighborPredicate.Instance<D extends Distance<D>> Instance for a particular data set.
static class	EpsilonNeighborPredicate.Parameterizer<O,D extends Distance<D>> Parameterization class

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan declared as Distance

Modifier and Type	Field and Description
protected D	EpsilonNeighborPredicate.epsilon Range to query with
(package private) D	EpsilonNeighborPredicate.Instance.epsilon Range to query with
(package private) D	EpsilonNeighborPredicate.Parameterizer.epsilon Range to query with

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

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical with type parameters of type Distance

Modifier and Type	Class and Description
class	ExtractFlatClusteringFromHierarchy<D extends Distance<D>> Extract a flat clustering from a full hierarchy, represented in pointer form.
private static class	ExtractFlatClusteringFromHierarchy.CompareByLambda<D extends Distance<D>> Order a DBID collection by the lambda value.
static class	ExtractFlatClusteringFromHierarchy.Parameterizer<D extends Distance<D>> Parameterization class.
interface	HierarchicalClusteringAlgorithm<D extends Distance<D>> Interface for hierarchical clustering algorithms.
class	PointerHierarchyRepresentationResult<D extends Distance<D>> The pointer representation of a hierarchical clustering.
class	SLINK<O,D extends Distance<D>> Implementation of the efficient Single-Link Algorithm SLINK of R.
static class	SLINK.Parameterizer<O,D extends Distance<D>> Parameterization class.

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical declared as Distance

Modifier and Type	Field and Description
private D	ExtractFlatClusteringFromHierarchy.threshold Threshold for extracting clusters.
(package private) D	ExtractFlatClusteringFromHierarchy.Parameterizer.threshold Threshold level.

Uses of Distance in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans with type parameters of type Distance

Modifier and Type	Class and Description
class	AbstractKMeans<V extends NumberVector<?>,D extends Distance<D>,M extends MeanModel<V>> Abstract base class for k-means implementations.
static class	AbstractKMeans.Parameterizer<V extends NumberVector<?>,D extends Distance<D>> Parameterization class.
class	BestOfMultipleKMeans<V extends NumberVector<?>,D extends Distance<?>,M extends MeanModel<V>> Run K-Means multiple times, and keep the best run.
static class	BestOfMultipleKMeans.Parameterizer<V extends NumberVector<?>,D extends Distance<D>,M extends MeanModel<V>> Parameterization class.
interface	KMeans<V extends NumberVector<?>,D extends Distance<?>,M extends MeanModel<V>> Some constants and options shared among kmeans family algorithms.
class	KMeansBatchedLloyd<V extends NumberVector<?>,D extends Distance<D>> Provides the k-means algorithm, using Lloyd-style bulk iterations.
static class	KMeansBatchedLloyd.Parameterizer<V extends NumberVector<?>,D extends Distance<D>> Parameterization class.
class	KMeansBisecting<V extends NumberVector<?>,D extends Distance<?>,M extends MeanModel<V>> The bisecting k-means algorithm works by starting with an initial partitioning into two clusters, then repeated splitting of the largest cluster to get additional clusters.
static class	KMeansBisecting.Parameterizer<V extends NumberVector<?>,D extends Distance<?>,M extends MeanModel<V>> Parameterization class.
class	KMeansHybridLloydMacQueen<V extends NumberVector<?>,D extends Distance<D>> Provides the k-means algorithm, alternating between MacQueen-style incremental processing and Lloyd-Style batch steps.
static class	KMeansHybridLloydMacQueen.Parameterizer<V extends NumberVector<?>,D extends Distance<D>> Parameterization class.
class	KMeansLloyd<V extends NumberVector<?>,D extends Distance<D>> Provides the k-means algorithm, using Lloyd-style bulk iterations.
static class	KMeansLloyd.Parameterizer<V extends NumberVector<?>,D extends Distance<D>> Parameterization class.
class	KMeansMacQueen<V extends NumberVector<?>,D extends Distance<D>> Provides the k-means algorithm, using MacQueen style incremental updates.
static class	KMeansMacQueen.Parameterizer<V extends NumberVector<?>,D extends Distance<D>> Parameterization class.
class	KMediansLloyd<V extends NumberVector<?>,D extends Distance<D>> Provides the k-medians clustering algorithm, using Lloyd-style bulk iterations.
static class	KMediansLloyd.Parameterizer<V extends NumberVector<?>,D extends Distance<D>> Parameterization class.
class	SampleKMeansInitialization<V extends NumberVector<?>,D extends Distance<?>> Initialize k-means by running k-means on a sample of the data set only.
static class	SampleKMeansInitialization.Parameterizer<V extends NumberVector<?>,D extends Distance<?>> Parameterization class.

Uses of Distance in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.quality with type parameters of type Distance

Modifier and Type	Interface and Description
interface	KMeansQualityMeasure<O extends NumberVector<?>,D extends Distance<?>> Interface for computing the quality of a K-Means clustering.

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

Classes in de.lmu.ifi.dbs.elki.algorithm.outlier with type parameters of type Distance

Modifier and Type	Class and Description
class	AbstractDBOutlier<O,D extends Distance<D>> Simple distance based outlier detection algorithms.
static class	AbstractDBOutlier.Parameterizer<O,D extends Distance<D>> Parameterization class.
class	DBOutlierDetection<O,D extends Distance<D>> Simple distanced based outlier detection algorithm.
static class	DBOutlierDetection.Parameterizer<O,D extends Distance<D>> Parameterization class.
class	DBOutlierScore<O,D extends Distance<D>> Compute percentage of neighbors in the given neighborhood with size d.
static class	DBOutlierScore.Parameterizer<O,D extends Distance<D>> Parameterization class.
class	ODIN<O,D extends Distance<D>> Outlier detection based on the in-degree of the kNN graph.
static class	ODIN.Parameterizer<O,D extends Distance<D>> Parameterization class.

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

Modifier and Type	Field and Description
private D	AbstractDBOutlier.d Holds the value of AbstractDBOutlier.D_ID.
protected D	AbstractDBOutlier.Parameterizer.d Query radius

Uses of Distance in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood

Classes in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood with type parameters of type Distance

Modifier and Type	Class and Description
class	PrecomputedKNearestNeighborNeighborhood<D extends Distance<D>> Neighborhoods based on k nearest neighbors.
static class	PrecomputedKNearestNeighborNeighborhood.Factory<O,D extends Distance<D>> Factory class to instantiate for a particular relation.
static class	PrecomputedKNearestNeighborNeighborhood.Factory.Parameterizer<O,D extends Distance<D>> Parameterization class

Uses of Distance in de.lmu.ifi.dbs.elki.data.model

Classes in de.lmu.ifi.dbs.elki.data.model with type parameters of type Distance

Modifier and Type	Class and Description
class	DendrogramModel<D extends Distance<D>> Model for dendrograms, provides the distance to the child cluster.

Fields in de.lmu.ifi.dbs.elki.data.model declared as Distance

Modifier and Type	Field and Description
private D	DendrogramModel.distance Distance to child cluster

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

Methods in de.lmu.ifi.dbs.elki.database with type parameters of type Distance

Modifier and Type	Method and Description
static <O,D extends Distance<D>> DistanceQuery<O,D>	QueryUtil.getDistanceQuery(Database database, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a distance query for a given distance function, automatically choosing a relation.
<O,D extends Distance<D>> DistanceQuery<O,D>	Database.getDistanceQuery(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get the distance query for a particular distance function.
<O,D extends Distance<D>> DistanceQuery<O,D>	AbstractDatabase.getDistanceQuery(Relation<O> objQuery, DistanceFunction<? super O,D> distanceFunction, Object... hints)
static <O,D extends Distance<D>> KNNQuery<O,D>	QueryUtil.getKNNQuery(Database database, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a KNN query object for the given distance function.
<O,D extends Distance<D>> KNNQuery<O,D>	Database.getKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints) Get a KNN query object for the given distance query.
<O,D extends Distance<D>> KNNQuery<O,D>	AbstractDatabase.getKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
static <O,D extends Distance<D>> KNNQuery<O,D>	QueryUtil.getKNNQuery(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a KNN query object for the given distance function.
static <O,D extends Distance<D>> KNNQuery<O,D>	QueryUtil.getLinearScanKNNQuery(DistanceQuery<O,D> distanceQuery) Get a linear scan query for the given distance query.
static <O,D extends Distance<D>> RangeQuery<O,D>	QueryUtil.getLinearScanRangeQuery(DistanceQuery<O,D> distanceQuery) Get a linear scan query for the given distance query.
static <O,D extends Distance<D>> RangeQuery<O,D>	QueryUtil.getRangeQuery(Database database, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a range query object for the given distance function.
<O,D extends Distance<D>> RangeQuery<O,D>	Database.getRangeQuery(DistanceQuery<O,D> distanceQuery, Object... hints) Get a range query object for the given distance query.
<O,D extends Distance<D>> RangeQuery<O,D>	AbstractDatabase.getRangeQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
static <O,D extends Distance<D>> RangeQuery<O,D>	QueryUtil.getRangeQuery(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a range query object for the given distance function.
<O,D extends Distance<D>> RKNNQuery<O,D>	Database.getRKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints) Get a rKNN query object for the given distance query.
<O,D extends Distance<D>> RKNNQuery<O,D>	AbstractDatabase.getRKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
static <O,D extends Distance<D>> RKNNQuery<O,D>	QueryUtil.getRKNNQuery(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, Object... hints) Get a rKNN query object for the given distance function.
static <O,D extends Distance<D>> SimilarityQuery<O,D>	QueryUtil.getSimilarityQuery(Database database, SimilarityFunction<? super O,D> similarityFunction, Object... hints) Get a similarity query, automatically choosing a relation.
<O,D extends Distance<D>> SimilarityQuery<O,D>	Database.getSimilarityQuery(Relation<O> relation, SimilarityFunction<? super O,D> similarityFunction, Object... hints) Get the similarity query for a particular similarity function.
<O,D extends Distance<D>> SimilarityQuery<O,D>	AbstractDatabase.getSimilarityQuery(Relation<O> objQuery, SimilarityFunction<? super O,D> similarityFunction, Object... hints)

Uses of Distance in de.lmu.ifi.dbs.elki.database.ids

Methods in de.lmu.ifi.dbs.elki.database.ids with type parameters of type Distance

Modifier and Type	Method and Description
<D extends Distance<D>> DistanceDBIDPair<D>	DBIDFactory.newDistancePair(D val, DBIDRef id) Make a new distance-DBID pair.
static <D extends Distance<D>> DistanceDBIDPair<D>	DBIDUtil.newDistancePair(D dist, DBIDRef id) Make a DistanceDBIDPair.
<D extends Distance<D>> KNNHeap<D>	DBIDFactory.newHeap(D factory, int k) Create an appropriate heap for the distance function.
static <D extends Distance<D>> KNNHeap<D>	DBIDUtil.newHeap(D distancetype, int k) Create an appropriate heap for the distance type.
<D extends Distance<D>> KNNHeap<D>	DBIDFactory.newHeap(KNNList<D> exist) Build a new heap from a given list.
static <D extends Distance<D>> KNNHeap<D>	DBIDUtil.newHeap(KNNList<D> exist) Build a new heap from a given list.
static <D extends Distance<D>> KNNList<D>	DBIDUtil.subList(KNNList<D> list, int k) Get a subset of the KNN result.

Uses of Distance in de.lmu.ifi.dbs.elki.database.ids.distance

Classes in de.lmu.ifi.dbs.elki.database.ids.distance with type parameters of type Distance

Modifier and Type	Interface and Description
interface	DistanceDBIDList<D extends Distance<D>> Collection of objects and their distances.
interface	DistanceDBIDListIter<D extends Distance<D>> Iterator over distance-based query results.
interface	DistanceDBIDPair<D extends Distance<D>> Pair containing a distance an an object ID Note: there is no getter for the object, as this is a DBIDRef.
interface	KNNHeap<D extends Distance<D>> Interface for kNN heaps.
interface	KNNList<D extends Distance<D>> Interface for kNN results.
interface	ModifiableDistanceDBIDList<D extends Distance<D>> Modifiable API for Distance-DBID results

Uses of Distance in de.lmu.ifi.dbs.elki.database.ids.generic

Classes in de.lmu.ifi.dbs.elki.database.ids.generic with type parameters of type Distance

Modifier and Type	Class and Description
(package private) class	AbstractKNNHeap<P extends DistanceDBIDPair<D>,D extends Distance<D>> Heap used for KNN management.
class	DistanceDBIDPairKNNHeap<D extends Distance<D>> Heap for collecting kNN candidates with arbitrary distance types.
class	DistanceDBIDPairKNNList<D extends Distance<D>> Finalized KNN List.
class	GenericDistanceDBIDList<D extends Distance<D>> Default class to keep a list of distance-object pairs.
class	KNNSubList<D extends Distance<D>> Sublist of an existing result to contain only the first k elements.

Fields in de.lmu.ifi.dbs.elki.database.ids.generic declared as Distance

Modifier and Type	Field and Description
protected D	DistanceDBIDPairKNNHeap.knndistance Cached distance to k nearest neighbor (to avoid going through AbstractKNNHeap.peek() each time).

Uses of Distance in de.lmu.ifi.dbs.elki.database.ids.integer

Classes in de.lmu.ifi.dbs.elki.database.ids.integer with type parameters of type Distance

Modifier and Type	Class and Description
(package private) class	DistanceIntegerDBIDPair<D extends Distance<D>> Class storing a double distance a DBID.

Fields in de.lmu.ifi.dbs.elki.database.ids.integer declared as Distance

Modifier and Type	Field and Description
(package private) D	DistanceIntegerDBIDPair.distance The distance value.

Methods in de.lmu.ifi.dbs.elki.database.ids.integer with type parameters of type Distance

Modifier and Type	Method and Description
<D extends Distance<D>> DistanceDBIDPair<D>	AbstractIntegerDBIDFactory.newDistancePair(D val, DBIDRef id)
<D extends Distance<D>> KNNHeap<D>	AbstractIntegerDBIDFactory.newHeap(D factory, int k)
<D extends Distance<D>> KNNHeap<D>	AbstractIntegerDBIDFactory.newHeap(KNNList<D> exist)

Uses of Distance in de.lmu.ifi.dbs.elki.database.query

Classes in de.lmu.ifi.dbs.elki.database.query with type parameters of type Distance

Modifier and Type	Interface and Description
interface	DistanceSimilarityQuery<O,D extends Distance<D>> Interface that is a combination of distance and a similarity function.

Uses of Distance in de.lmu.ifi.dbs.elki.database.query.distance

Classes in de.lmu.ifi.dbs.elki.database.query.distance with type parameters of type Distance

Modifier and Type	Class and Description
class	AbstractDatabaseDistanceQuery<O,D extends Distance<D>> Run a database query in a database context.
class	AbstractDistanceQuery<O,D extends Distance<D>> A distance query serves as adapter layer for database and primitive distances.
class	DBIDDistanceQuery<D extends Distance<D>> Run a distance query based on DBIDs
interface	DistanceQuery<O,D extends Distance<?>> A distance query serves as adapter layer for database and primitive distances.
class	PrimitiveDistanceQuery<O,D extends Distance<D>> Run a database query in a database context.
class	PrimitiveDistanceSimilarityQuery<O,D extends Distance<D>> Combination query class, for convenience.
interface	SpatialDistanceQuery<V extends SpatialComparable,D extends Distance<D>> Query interface for spatial distance queries.
class	SpatialPrimitiveDistanceQuery<V extends SpatialComparable,D extends Distance<D>> Distance query for spatial distance functions

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

Classes in de.lmu.ifi.dbs.elki.database.query.knn with type parameters of type Distance

Modifier and Type	Class and Description
class	AbstractDistanceKNNQuery<O,D extends Distance<D>> Instance for the query on a particular database.
interface	KNNQuery<O,D extends Distance<D>> The interface of an actual instance.
class	LinearScanDistanceKNNQuery<O,D extends Distance<D>> Instance of this query for a particular database.
class	LinearScanPrimitiveDistanceKNNQuery<O,D extends Distance<D>> Instance of this query for a particular database.
class	PreprocessorKNNQuery<O,D extends Distance<D>,T extends KNNList<D>> Instance for a particular database, invoking the preprocessor.

Uses of Distance in de.lmu.ifi.dbs.elki.database.query.range

Classes in de.lmu.ifi.dbs.elki.database.query.range with type parameters of type Distance

Modifier and Type	Class and Description
class	AbstractDistanceRangeQuery<O,D extends Distance<D>> Abstract base class for range queries that use a distance query in their instance
class	LinearScanDistanceRangeQuery<O,D extends Distance<D>> Default linear scan range query class.
class	LinearScanPrimitiveDistanceRangeQuery<O,D extends Distance<D>> Default linear scan range query class.
interface	RangeQuery<O,D extends Distance<D>> The interface for range queries

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

Classes in de.lmu.ifi.dbs.elki.database.query.rknn with type parameters of type Distance

Modifier and Type	Class and Description
class	AbstractRKNNQuery<O,D extends Distance<D>> Instance for the query on a particular database.
class	LinearScanRKNNQuery<O,D extends Distance<D>> Default linear scan RKNN query class.
class	PreprocessorRKNNQuery<O,D extends Distance<D>> Instance for a particular database, invoking the preprocessor.
interface	RKNNQuery<O,D extends Distance<D>> Abstract reverse kNN Query interface.

Uses of Distance in de.lmu.ifi.dbs.elki.database.query.similarity

Classes in de.lmu.ifi.dbs.elki.database.query.similarity with type parameters of type Distance

Modifier and Type	Class and Description
class	AbstractDBIDSimilarityQuery<O,D extends Distance<D>> Run a database query in a database context.
class	AbstractSimilarityQuery<O,D extends Distance<D>> A distance query serves as adapter layer for database and primitive similarity functions.
class	PrimitiveSimilarityQuery<O,D extends Distance<D>> Run a database query in a database context.
interface	SimilarityQuery<O,D extends Distance<?>> A similarity query serves as adapter layer for database and primitive similarity functions.

Uses of Distance in de.lmu.ifi.dbs.elki.distance

Methods in de.lmu.ifi.dbs.elki.distance with type parameters of type Distance

Modifier and Type	Method and Description
static <D extends Distance<D>> D	DistanceUtil.max(D d1, D d2) Returns the maximum of the given Distances or the first, if none is greater than the other one.
static <D extends Distance<D>> D	DistanceUtil.min(D d1, D d2) Returns the minimum of the given Distances or the first, if none is less than the other one.

Uses of Distance in de.lmu.ifi.dbs.elki.distance.distancefunction

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction with type parameters of type Distance

Modifier and Type	Class and Description
class	AbstractDatabaseDistanceFunction<O,D extends Distance<D>> Abstract super class for distance functions needing a database context.
static class	AbstractDatabaseDistanceFunction.Instance<O,D extends Distance<D>> The actual instance bound to a particular database.
class	AbstractDBIDDistanceFunction<D extends Distance<D>> AbstractDistanceFunction provides some methods valid for any extending class.
class	AbstractIndexBasedDistanceFunction<O,I extends Index,D extends Distance<D>> Abstract super class for distance functions needing a database index.
static class	AbstractIndexBasedDistanceFunction.Instance<O,I extends Index,D extends Distance<D>,F extends DistanceFunction<? super O,D>> The actual instance bound to a particular database.
class	AbstractPrimitiveDistanceFunction<O,D extends Distance<D>> AbstractDistanceFunction provides some methods valid for any extending class.
interface	DBIDDistanceFunction<D extends Distance<?>> Distance functions valid in a database context only (i.e. for DBIDs) For any "distance" that cannot be computed for arbitrary objects, only those that exist in the database and referenced by their ID.
interface	DistanceFunction<O,D extends Distance<?>> Base interface for any kind of distances.
interface	FilteredLocalPCABasedDistanceFunction<O extends NumberVector<?>,P extends FilteredLocalPCAIndex<? super O>,D extends Distance<D>> Interface for local PCA based preprocessors.
static interface	FilteredLocalPCABasedDistanceFunction.Instance<T extends NumberVector<?>,I extends Index,D extends Distance<D>> Instance produced by the distance function.
interface	IndexBasedDistanceFunction<O,D extends Distance<D>> Distance function relying on an index (such as preprocessed neighborhoods).
static interface	IndexBasedDistanceFunction.Instance<T,I extends Index,D extends Distance<D>> Instance interface for Index based distance functions.
class	MinKDistance<O,D extends Distance<D>> A distance that is at least the distance to the kth nearest neighbor.
static class	MinKDistance.Parameterizer<O,D extends Distance<D>> Parameterization class.
interface	Norm<O,D extends Distance<D>> Abstract interface for a mathematical norm.
interface	NumberVectorDistanceFunction<D extends Distance<D>> Base interface for the common case of distance functions defined on numerical vectors.
interface	PrimitiveDistanceFunction<O,D extends Distance<?>> Primitive distance function that is defined on some kind of object.
class	ProxyDistanceFunction<O,D extends Distance<D>> Distance function to proxy computations to another distance (that probably was run before).
interface	SpatialPrimitiveDistanceFunction<V extends SpatialComparable,D extends Distance<D>> API for a spatial primitive distance function.

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction with type parameters of type Distance

Modifier and Type	Method and Description
static <O,D extends Distance<D>> ProxyDistanceFunction<O,D>	ProxyDistanceFunction.proxy(DistanceQuery<O,D> inner) Static method version.
static <V,T extends V,D extends Distance<D>> DistanceFunction<? super V,D>	ProxyDistanceFunction.unwrapDistance(DistanceFunction<V,D> dfun) Helper function, to resolve any wrapped Proxy Distances

Uses of Distance in de.lmu.ifi.dbs.elki.distance.distancefunction.external

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.external with type parameters of type Distance

Modifier and Type	Interface and Description
interface	DistanceParser<D extends Distance<D>> A DistanceParser shall provide a DistanceParsingResult by parsing an InputStream.
class	DistanceParsingResult<D extends Distance<D>> Provides a cache of precomputed distances between the database objects.

Uses of Distance in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace with type parameters of type Distance

Modifier and Type	Interface and Description
interface	DimensionSelectingSubspaceDistanceFunction<O,D extends Distance<D>> Interface for dimension selecting subspace distance functions.

Uses of Distance in de.lmu.ifi.dbs.elki.distance.distancevalue

Classes in de.lmu.ifi.dbs.elki.distance.distancevalue with type parameters of type Distance

Modifier and Type	Interface and Description
interface	Distance<D extends Distance<D>> The interface Distance defines the requirements of any instance class.

Classes in de.lmu.ifi.dbs.elki.distance.distancevalue that implement Distance

Modifier and Type	Class and Description
class	AbstractDistance<D extends AbstractDistance<D>> An abstract distance implements equals conveniently for any extending class.
class	BitDistance Provides a Distance for a bit-valued distance.
class	CorrelationDistance<D extends CorrelationDistance<D>> The correlation distance is a special Distance that indicates the dissimilarity between correlation connected objects.
class	DoubleDistance Provides a Distance for a double-valued distance.
class	FloatDistance Provides a Distance for a float-valued distance.
class	IntegerDistance Provides an integer distance value.
class	NumberDistance<D extends NumberDistance<D,N>,N extends Number> Provides a Distance for a number-valued distance.
class	PCACorrelationDistance The correlation distance is a special Distance that indicates the dissimilarity between correlation connected objects.
class	PreferenceVectorBasedCorrelationDistance A PreferenceVectorBasedCorrelationDistance holds additionally to the CorrelationDistance the common preference vector of the two objects defining the distance.
class	SubspaceDistance The subspace distance is a special distance that indicates the dissimilarity between subspaces of equal dimensionality.

Uses of Distance in de.lmu.ifi.dbs.elki.distance.similarityfunction

Classes in de.lmu.ifi.dbs.elki.distance.similarityfunction with type parameters of type Distance

Modifier and Type	Class and Description
class	AbstractDBIDSimilarityFunction<D extends Distance<D>> Abstract super class for distance functions needing a preprocessor.
class	AbstractIndexBasedSimilarityFunction<O,I extends Index,R,D extends Distance<D>> Abstract super class for distance functions needing a preprocessor.
static class	AbstractIndexBasedSimilarityFunction.Instance<O,I extends Index,R,D extends Distance<D>> The actual instance bound to a particular database.
class	AbstractPrimitiveSimilarityFunction<O,D extends Distance<D>> Base implementation of a similarity function.
interface	DBIDSimilarityFunction<D extends Distance<D>> Interface DBIDSimilarityFunction describes the requirements of any similarity function defined over object IDs.
interface	IndexBasedSimilarityFunction<O,D extends Distance<D>> Interface for preprocessor/index based similarity functions.
static interface	IndexBasedSimilarityFunction.Instance<T,I extends Index,D extends Distance<D>> Instance interface for index/preprocessor based distance functions.
interface	PrimitiveSimilarityFunction<O,D extends Distance<?>> Interface SimilarityFunction describes the requirements of any similarity function.
interface	SimilarityFunction<O,D extends Distance<?>> Interface SimilarityFunction describes the requirements of any similarity function.

Uses of Distance in de.lmu.ifi.dbs.elki.evaluation.roc

Classes in de.lmu.ifi.dbs.elki.evaluation.roc with type parameters of type Distance

Modifier and Type	Class and Description
static class	ROC.DistanceResultAdapter<D extends Distance<D>> This adapter can be used for an arbitrary collection of Integers, and uses that id1.compareTo(id2) !

Fields in de.lmu.ifi.dbs.elki.evaluation.roc declared as Distance

Modifier and Type	Field and Description
private D	ROC.DistanceResultAdapter.prevDist Distance of previous.

Methods in de.lmu.ifi.dbs.elki.evaluation.roc with type parameters of type Distance

Modifier and Type	Method and Description
static <D extends Distance<D>> double	ROC.computeROCAUCDistanceResult(int size, Cluster<?> clus, DistanceDBIDList<D> nei) Compute a ROC curves Area-under-curve for a QueryResult and a Cluster.
static <D extends Distance<D>> double	ROC.computeROCAUCDistanceResult(int size, DBIDs ids, DistanceDBIDList<D> nei) Compute a ROC curves Area-under-curve for a QueryResult and a Cluster.

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

Classes in de.lmu.ifi.dbs.elki.index with type parameters of type Distance

Modifier and Type	Class and Description
class	AbstractRefiningIndex.AbstractKNNQuery<D extends Distance<D>> KNN query for this index.
class	AbstractRefiningIndex.AbstractRangeQuery<D extends Distance<D>> Range query for this index.

Methods in de.lmu.ifi.dbs.elki.index with type parameters of type Distance

Modifier and Type	Method and Description
<D extends Distance<D>> KNNQuery<O,D>	KNNIndex.getKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints) Get a KNN query object for the given distance query and k.
<D extends Distance<D>> RangeQuery<O,D>	RangeIndex.getRangeQuery(DistanceQuery<O,D> distanceQuery, Object... hints) Get a range query object for the given distance query and k.
<D extends Distance<D>> RKNNQuery<O,D>	RKNNIndex.getRKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints) Get a KNN query object for the given distance query and k.

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

Classes in de.lmu.ifi.dbs.elki.index.lsh with type parameters of type Distance

Modifier and Type	Class and Description
protected class	InMemoryLSHIndex.Instance.LSHKNNQuery<D extends Distance<D>> Class for handling kNN queries against the LSH index.
protected class	InMemoryLSHIndex.Instance.LSHRangeQuery<D extends Distance<D>> Class for handling kNN queries against the LSH index.

Methods in de.lmu.ifi.dbs.elki.index.lsh with type parameters of type Distance

Modifier and Type	Method and Description
<D extends Distance<D>> KNNQuery<V,D>	InMemoryLSHIndex.Instance.getKNNQuery(DistanceQuery<V,D> distanceQuery, Object... hints)
<D extends Distance<D>> RangeQuery<V,D>	InMemoryLSHIndex.Instance.getRangeQuery(DistanceQuery<V,D> distanceQuery, Object... hints)

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

Classes in de.lmu.ifi.dbs.elki.index.preprocessed.knn with type parameters of type Distance

Modifier and Type	Class and Description
class	AbstractMaterializeKNNPreprocessor<O,D extends Distance<D>,T extends KNNList<D>> Abstract base class for KNN Preprocessors.
static class	AbstractMaterializeKNNPreprocessor.Factory<O,D extends Distance<D>,T extends KNNList<D>> The parameterizable factory.
static class	AbstractMaterializeKNNPreprocessor.Factory.Parameterizer<O,D extends Distance<D>> Parameterization class.
class	KNNJoinMaterializeKNNPreprocessor<V extends NumberVector<?>,D extends Distance<D>> Class to materialize the kNN using a spatial join on an R-tree.
static class	KNNJoinMaterializeKNNPreprocessor.Factory<O extends NumberVector<?>,D extends Distance<D>> The parameterizable factory.
static class	KNNJoinMaterializeKNNPreprocessor.Factory.Parameterizer<O extends NumberVector<?>,D extends Distance<D>> Parameterization class
class	MaterializeKNNAndRKNNPreprocessor<O,D extends Distance<D>> A preprocessor for annotation of the k nearest neighbors and the reverse k nearest neighbors (and their distances) to each database object.
static class	MaterializeKNNAndRKNNPreprocessor.Factory<O,D extends Distance<D>> The parameterizable factory.
static class	MaterializeKNNAndRKNNPreprocessor.Factory.Parameterizer<O,D extends Distance<D>> Parameterization class.
class	MaterializeKNNPreprocessor<O,D extends Distance<D>> A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
static class	MaterializeKNNPreprocessor.Factory<O,D extends Distance<D>> The parameterizable factory.
static class	MaterializeKNNPreprocessor.Factory.Parameterizer<O,D extends Distance<D>> Parameterization class.
class	MetricalIndexApproximationMaterializeKNNPreprocessor<O extends NumberVector<?>,D extends Distance<D>,N extends Node<E>,E extends MTreeEntry> A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
static class	MetricalIndexApproximationMaterializeKNNPreprocessor.Factory<O extends NumberVector<?>,D extends Distance<D>,N extends Node<E>,E extends MTreeEntry> The parameterizable factory.
static class	MetricalIndexApproximationMaterializeKNNPreprocessor.Factory.Parameterizer<O extends NumberVector<?>,D extends Distance<D>,N extends Node<E>,E extends MTreeEntry> Parameterization class.
class	PartitionApproximationMaterializeKNNPreprocessor<O,D extends Distance<D>> A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
static class	PartitionApproximationMaterializeKNNPreprocessor.Factory<O,D extends Distance<D>> The parameterizable factory.
static class	PartitionApproximationMaterializeKNNPreprocessor.Factory.Parameterizer<O,D extends Distance<D>> Parameterization class.
class	RandomSampleKNNPreprocessor<O,D extends Distance<D>> Class that computed the kNN only on a random sample.
static class	RandomSampleKNNPreprocessor.Factory<O,D extends Distance<D>> The parameterizable factory.
static class	RandomSampleKNNPreprocessor.Factory.Parameterizer<O,D extends Distance<D>> Parameterization class
class	SpatialApproximationMaterializeKNNPreprocessor<O extends NumberVector<?>,D extends Distance<D>,N extends SpatialNode<N,E>,E extends SpatialEntry> A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
static class	SpatialApproximationMaterializeKNNPreprocessor.Factory<D extends Distance<D>,N extends SpatialNode<N,E>,E extends SpatialEntry> The actual preprocessor instance.
static class	SpatialApproximationMaterializeKNNPreprocessor.Factory.Parameterizer<D extends Distance<D>,N extends SpatialNode<N,E>,E extends SpatialEntry> Parameterization class.

Methods in de.lmu.ifi.dbs.elki.index.preprocessed.knn with type parameters of type Distance

Modifier and Type	Method and Description
<S extends Distance<S>> KNNQuery<O,S>	AbstractMaterializeKNNPreprocessor.getKNNQuery(DistanceQuery<O,S> distQ, Object... hints)
<S extends Distance<S>> RKNNQuery<O,S>	MaterializeKNNAndRKNNPreprocessor.getRKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)

Uses of Distance in de.lmu.ifi.dbs.elki.index.preprocessed.snn

Classes in de.lmu.ifi.dbs.elki.index.preprocessed.snn with type parameters of type Distance

Modifier and Type	Class and Description
class	SharedNearestNeighborPreprocessor<O,D extends Distance<D>> A preprocessor for annotation of the ids of nearest neighbors to each database object.
static class	SharedNearestNeighborPreprocessor.Factory<O,D extends Distance<D>> Factory class
static class	SharedNearestNeighborPreprocessor.Factory.Parameterizer<O,D extends Distance<D>> Parameterization class.

Uses of Distance in de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj

Classes in de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj with type parameters of type Distance

Modifier and Type	Class and Description
class	AbstractSubspaceProjectionIndex<NV extends NumberVector<?>,D extends Distance<D>,P extends ProjectionResult> Abstract base class for a local PCA based index.
static class	AbstractSubspaceProjectionIndex.Factory<NV extends NumberVector<?>,D extends Distance<D>,I extends AbstractSubspaceProjectionIndex<NV,D,?>> Factory class
static class	AbstractSubspaceProjectionIndex.Factory.Parameterizer<NV extends NumberVector<?>,D extends Distance<D>,C> Parameterization class.
class	FourCSubspaceIndex<V extends NumberVector<?>,D extends Distance<D>> Preprocessor for 4C local dimensionality and locally weighted matrix assignment to objects of a certain database.
static class	FourCSubspaceIndex.Factory<V extends NumberVector<?>,D extends Distance<D>> Factory class for 4C preprocessors.
static class	FourCSubspaceIndex.Factory.Parameterizer<V extends NumberVector<?>,D extends Distance<D>> Parameterization class.
class	PreDeConSubspaceIndex<V extends NumberVector<?>,D extends Distance<D>> Preprocessor for PreDeCon local dimensionality and locally weighted matrix assignment to objects of a certain database.
static class	PreDeConSubspaceIndex.Factory<V extends NumberVector<?>,D extends Distance<D>> Factory.
static class	PreDeConSubspaceIndex.Factory.Parameterizer<V extends NumberVector<?>,D extends Distance<D>> Parameterization class.

Fields in de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj declared as Distance

Modifier and Type	Field and Description
protected D	AbstractSubspaceProjectionIndex.epsilon Contains the value of parameter epsilon;
protected D	AbstractSubspaceProjectionIndex.Factory.epsilon Contains the value of parameter epsilon;
protected D	AbstractSubspaceProjectionIndex.Factory.Parameterizer.epsilon Contains the value of parameter epsilon;

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

Classes in de.lmu.ifi.dbs.elki.index.projected with type parameters of type Distance

Modifier and Type	Class and Description
(package private) class	ProjectedIndex.ProjectedKNNQuery<D extends Distance<D>> Class to proxy kNN queries.
(package private) class	ProjectedIndex.ProjectedRangeQuery<D extends Distance<D>> Class to proxy range queries.
(package private) class	ProjectedIndex.ProjectedRKNNQuery<D extends Distance<D>> Class to proxy RkNN queries.

Methods in de.lmu.ifi.dbs.elki.index.projected with type parameters of type Distance

Modifier and Type	Method and Description
<D extends Distance<D>> KNNQuery<O,D>	LatLngAsECEFIndex.getKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<D extends Distance<D>> KNNQuery<O,D>	ProjectedIndex.getKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<D extends Distance<D>> KNNQuery<O,D>	LngLatAsECEFIndex.getKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<D extends Distance<D>> RangeQuery<O,D>	LatLngAsECEFIndex.getRangeQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<D extends Distance<D>> RangeQuery<O,D>	ProjectedIndex.getRangeQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<D extends Distance<D>> RangeQuery<O,D>	LngLatAsECEFIndex.getRangeQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<D extends Distance<D>> RKNNQuery<O,D>	LatLngAsECEFIndex.getRKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<D extends Distance<D>> RKNNQuery<O,D>	ProjectedIndex.getRKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<D extends Distance<D>> RKNNQuery<O,D>	LngLatAsECEFIndex.getRKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints)

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

Classes in de.lmu.ifi.dbs.elki.index.tree.metrical with type parameters of type Distance

Modifier and Type	Class and Description
class	MetricalIndexTree<O,D extends Distance<D>,N extends Node<E>,E extends Entry> Abstract super class for all metrical index classes.

Uses of Distance 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 with type parameters of type Distance

Modifier and Type	Method and Description
<S extends Distance<S>> KNNQuery<O,S>	MkAppTreeIndex.getKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RangeQuery<O,S>	MkAppTreeIndex.getRangeQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RKNNQuery<O,S>	MkAppTreeIndex.getRKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)

Uses of Distance 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 with type parameters of type Distance

Modifier and Type	Method and Description
<S extends Distance<S>> KNNQuery<O,S>	MkCoPTreeIndex.getKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RangeQuery<O,S>	MkCoPTreeIndex.getRangeQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RKNNQuery<O,S>	MkCoPTreeIndex.getRKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)

Uses of Distance 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 with type parameters of type Distance

Modifier and Type	Method and Description
<S extends Distance<S>> KNNQuery<O,S>	MkMaxTreeIndex.getKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RangeQuery<O,S>	MkMaxTreeIndex.getRangeQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RKNNQuery<O,S>	MkMaxTreeIndex.getRKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)

Uses of Distance 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 with type parameters of type Distance

Modifier and Type	Method and Description
<S extends Distance<S>> KNNQuery<O,S>	MkTabTreeIndex.getKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RangeQuery<O,S>	MkTabTreeIndex.getRangeQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RKNNQuery<O,S>	MkTabTreeIndex.getRKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)

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

Methods in de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree with type parameters of type Distance

Modifier and Type	Method and Description
<S extends Distance<S>> KNNQuery<O,S>	MTreeIndex.getKNNQuery(DistanceQuery<O,S> distanceQuery, Object... hints)
<S extends Distance<S>> RangeQuery<O,S>	MTreeIndex.getRangeQuery(DistanceQuery<O,S> distanceQuery, Object... hints)

Uses of Distance in de.lmu.ifi.dbs.elki.index.tree.query

Classes in de.lmu.ifi.dbs.elki.index.tree.query with type parameters of type Distance

Modifier and Type	Class and Description
class	GenericDistanceSearchCandidate<D extends Distance<D>> Candidate for expansion in a distance search (generic implementation).

Fields in de.lmu.ifi.dbs.elki.index.tree.query declared as Distance

Modifier and Type	Field and Description
D	GenericDistanceSearchCandidate.mindist Distance value

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

Methods in de.lmu.ifi.dbs.elki.index.tree.spatial.kd with type parameters of type Distance

Modifier and Type	Method and Description
<D extends Distance<D>> KNNQuery<O,D>	MinimalisticMemoryKDTree.getKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<D extends Distance<D>> RangeQuery<O,D>	MinimalisticMemoryKDTree.getRangeQuery(DistanceQuery<O,D> distanceQuery, Object... hints)

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

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

Modifier and Type	Method and Description
<D extends Distance<D>> KNNQuery<O,D>	DeLiCluTreeIndex.getKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<D extends Distance<D>> RangeQuery<O,D>	DeLiCluTreeIndex.getRangeQuery(DistanceQuery<O,D> distanceQuery, Object... hints)

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

Classes in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query with type parameters of type Distance

Modifier and Type	Class and Description
class	GenericRStarTreeKNNQuery<O extends SpatialComparable,D extends Distance<D>> Instance of a KNN query for a particular spatial index.
class	GenericRStarTreeRangeQuery<O extends SpatialComparable,D extends Distance<D>> Instance of a range query for a particular spatial index.

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

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

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

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

Modifier and Type	Method and Description
<D extends Distance<D>> KNNQuery<O,D>	RStarTreeIndex.getKNNQuery(DistanceQuery<O,D> distanceQuery, Object... hints)
<D extends Distance<D>> RangeQuery<O,D>	RStarTreeIndex.getRangeQuery(DistanceQuery<O,D> distanceQuery, Object... hints)

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

Methods in de.lmu.ifi.dbs.elki.index.vafile with type parameters of type Distance

Modifier and Type	Method and Description
<D extends Distance<D>> KNNQuery<V,D>	PartialVAFile.getKNNQuery(DistanceQuery<V,D> distanceQuery, Object... hints)
<D extends Distance<D>> KNNQuery<V,D>	VAFile.getKNNQuery(DistanceQuery<V,D> distanceQuery, Object... hints)
<D extends Distance<D>> RangeQuery<V,D>	PartialVAFile.getRangeQuery(DistanceQuery<V,D> distanceQuery, Object... hints)
<D extends Distance<D>> RangeQuery<V,D>	VAFile.getRangeQuery(DistanceQuery<V,D> distanceQuery, Object... hints)

Uses of Distance in de.lmu.ifi.dbs.elki.result

Classes in de.lmu.ifi.dbs.elki.result with type parameters of type Distance

Modifier and Type	Class and Description
class	KNNDistanceOrderResult<D extends Distance<D>> Wraps a list containing the knn distances.

Uses of Distance in de.lmu.ifi.dbs.elki.result.optics

Classes in de.lmu.ifi.dbs.elki.result.optics with type parameters of type Distance

Modifier and Type	Interface and Description
interface	ClusterOrderEntry<D extends Distance<D>> Generic Cluster Order Entry Interface.
class	ClusterOrderResult<D extends Distance<D>> Class to store the result of an ordering clustering algorithm such as OPTICS.
class	GenericClusterOrderEntry<D extends Distance<D>> Provides an entry in a cluster order.

Fields in de.lmu.ifi.dbs.elki.result.optics declared as Distance

Modifier and Type	Field and Description
private D	GenericClusterOrderEntry.reachability The reachability of the entry.

Uses of Distance in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters

Classes in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters with type parameters of type Distance

Modifier and Type	Class and Description
class	DistanceParameter<D extends Distance<D>> Parameter class for a parameter specifying a double value.

Fields in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters declared as Distance

Modifier and Type	Field and Description
(package private) D	DistanceParameter.dist Distance type

Uses of Distance in de.lmu.ifi.dbs.elki.visualization.opticsplot

Classes in de.lmu.ifi.dbs.elki.visualization.opticsplot with type parameters of type Distance

Modifier and Type	Interface and Description
interface	OPTICSDistanceAdapter<D extends Distance<D>> Interface to map ClusterOrderEntries to double values to use in the OPTICS plot.
class	OPTICSPlot<D extends Distance<D>> Class to produce an OPTICS plot image.

Methods in de.lmu.ifi.dbs.elki.visualization.opticsplot with type parameters of type Distance

Modifier and Type	Method and Description
static <D extends Distance<D>> boolean	OPTICSPlot.canPlot(ClusterOrderResult<D> co) Test whether this class can produce an OPTICS plot for the given cluster order.
private static <D extends Distance<D>> OPTICSDistanceAdapter<D>	OPTICSPlot.getAdapterForDistance(ClusterOrderResult<D> co) Try to find a distance adapter.
static <D extends Distance<D>> Clustering<Model>	OPTICSCut.makeOPTICSCut(ClusterOrderResult<D> co, OPTICSDistanceAdapter<D> adapter, double epsilon) Compute an OPTICS cut clustering
static <D extends Distance<D>> OPTICSPlot<D>	OPTICSPlot.plotForClusterOrder(ClusterOrderResult<D> co, VisualizerContext context) Static method to find an optics plot for a result, or to create a new one using the given context.

Uses of Distance in de.lmu.ifi.dbs.elki.visualization.projections

Classes in de.lmu.ifi.dbs.elki.visualization.projections with type parameters of type Distance

Modifier and Type	Class and Description
class	OPTICSProjection<D extends Distance<D>> OPTICS projection.

Uses of Distance in de.lmu.ifi.dbs.elki.visualization.projector

Classes in de.lmu.ifi.dbs.elki.visualization.projector with type parameters of type Distance

Modifier and Type	Class and Description
class	OPTICSProjector<D extends Distance<D>> Projection for OPTICS plots.

Uses of Distance in de.lmu.ifi.dbs.elki.visualization.visualizers.optics

Classes in de.lmu.ifi.dbs.elki.visualization.visualizers.optics with type parameters of type Distance

Modifier and Type	Class and Description
class	AbstractOPTICSVisualization<D extends Distance<D>> Abstract base class for OPTICS visualizer
class	OPTICSClusterVisualization.Instance<D extends Distance<D>> Instance.
class	OPTICSPlotCutVisualization.Instance<D extends Distance<D>> Instance.
class	OPTICSPlotSelectionVisualization.Instance<D extends Distance<D>> Instance.
class	OPTICSPlotVisualizer.Instance<D extends Distance<D>> Instance.
class	OPTICSSteepAreaVisualization.Instance<D extends Distance<D>> Instance

Uses of Distance in tutorial.outlier

Classes in tutorial.outlier with type parameters of type Distance

Modifier and Type	Class and Description
class	ODIN<O,D extends Distance<D>> Outlier detection based on the in-degree of the kNN graph.
static class	ODIN.Parameterizer<O,D extends Distance<D>> Parameterization class.