Uses of Interface
elki.distance.Distance
-
Packages that use Distance Package Description elki.algorithm Miscellaneous algorithms.elki.algorithm.statistics Statistical analysis algorithms.elki.application Base classes for standalone applications.elki.application.benchmark Benchmarking pseudo algorithms.elki.application.cache Utility applications for the persistence layer such as distance cache builders.elki.application.greedyensemble Greedy ensembles for outlier detection.elki.application.statistics Applications to compute some basic data set statistics.elki.classification Classification algorithms.elki.clustering Clustering algorithms.elki.clustering.affinitypropagation Affinity Propagation (AP) clustering.elki.clustering.dbscan DBSCAN and its generalizations.elki.clustering.dbscan.predicates Neighbor and core predicated for Generalized DBSCAN.elki.clustering.hierarchical Hierarchical agglomerative clustering (HAC).elki.clustering.kcenter K-center clustering.elki.clustering.kmedoids K-medoids clustering (PAM).elki.clustering.optics OPTICS family of clustering algorithms.elki.clustering.silhouette Silhouette clustering algorithms.elki.database.query Database queries - computing distances, neighbors, similarities - API and general documentation.elki.database.query.distance Prepared queries for distances.elki.distance Distance functions for use within ELKI.elki.distance.adapter Distance functions deriving distances from, e.g., similarity measures.elki.distance.colorhistogram Distance functions for color histograms.elki.distance.correlation Distance functions using correlations.elki.distance.external Distance functions using external data sources.elki.distance.geo Geographic (earth) distance functions.elki.distance.histogram Distance functions for one-dimensional histograms.elki.distance.minkowski Minkowski space Lp norms such as the popular Euclidean and Manhattan distances.elki.distance.probabilistic Distance from probability theory, mostly divergences such as K-L-divergence, J-divergence, F-divergence, χ²-divergence, etc.elki.distance.set Distance functions for binary and set type data.elki.distance.strings Distance functions for strings.elki.distance.subspace Distance functions based on subspaces.elki.distance.timeseries Distance functions designed for time series.elki.evaluation.clustering.internal Internal evaluation measures for clusterings.elki.evaluation.similaritymatrix Render a distance matrix to visualize a clustering-distance-combination.elki.index Index structure implementations.elki.index.distancematrix Precomputed distance matrix.elki.index.idistance iDistance is a distance based indexing technique, using a reference points embedding.elki.index.laesa Linear Approximating and Eliminating Search Algorithm (LAESA).elki.index.lsh.hashfamilies Hash function families for LSH.elki.index.preprocessed.knn Indexes providing KNN and rKNN data.elki.index.preprocessed.snn Indexes providing nearest neighbor sets.elki.index.tree.metrical Tree-based index structures for metrical vector spaces.elki.index.tree.metrical.covertree Cover-tree variations.elki.index.tree.metrical.mtreevariants M-tree and variants.elki.index.tree.metrical.vptree elki.outlier Outlier detection algorithms.elki.outlier.clustering Clustering based outlier detection.elki.outlier.distance Distance-based outlier detection algorithms, such as DBOutlier and kNN.elki.outlier.distance.parallel Parallel implementations of distance-based outlier detectors.elki.outlier.intrinsic Outlier detection algorithms based on intrinsic dimensionality.elki.outlier.lof LOF family of outlier detection algorithms.elki.outlier.lof.parallel Parallelized variants of LOF.elki.outlier.spatial Spatial outlier detection algorithms.elki.outlier.spatial.neighborhood Spatial outlier neighborhood classes.elki.projection Data projections (see also preprocessing filters for basic projections).elki.similarity Similarity functions.elki.similarity.cluster Similarity measures for comparing clusters.elki.similarity.kernel Kernel functions.tutorial.clustering Classes from the tutorial on implementing a custom k-means variation.tutorial.distancefunction Classes from the tutorial on implementing distance functions.tutorial.outlier Tutorials on implementing outlier detection methods in ELKI. -
-
Uses of Distance in elki.algorithm
Fields in elki.algorithm declared as Distance Modifier and Type Field Description protected Distance<? super O>
KNNDistancesSampler. distance
Distance function used.protected Distance<? super O>
KNNDistancesSampler.Par. distance
The distance function to use.Constructors in elki.algorithm with parameters of type Distance Constructor Description KNNDistancesSampler(Distance<? super O> distance, int k, double sample, RandomFactory rnd)
Constructor. -
Uses of Distance in elki.algorithm.statistics
Fields in elki.algorithm.statistics declared as Distance Modifier and Type Field Description private Distance<? super O>
AveragePrecisionAtK. distance
Distance function used.protected Distance<? super O>
AveragePrecisionAtK.Par. distance
The distance function to use.private Distance<? super O>
DistanceQuantileSampler. distance
Distance function used.protected Distance<? super O>
DistanceQuantileSampler.Par. distance
The distance function to use.protected Distance<? super O>
DistanceStatisticsWithClasses. distance
Distance function used.protected Distance<? super O>
DistanceStatisticsWithClasses.Par. distance
The distance function to use.protected Distance<? super V>
EvaluateRankingQuality. distance
Distance function used.protected Distance<? super V>
EvaluateRankingQuality.Par. distance
The distance function to use.protected Distance<? super O>
EvaluateRetrievalPerformance. distance
Distance function used.protected Distance<? super O>
EvaluateRetrievalPerformance.Par. distance
The distance function to use.protected Distance<? super O>
RankingQualityHistogram. distance
Distance function used.protected Distance<? super O>
RankingQualityHistogram.Par. distance
The distance function to use.Constructors in elki.algorithm.statistics with parameters of type Distance Constructor Description AveragePrecisionAtK(Distance<? super O> distance, int k, double sampling, RandomFactory random, boolean includeSelf)
Constructor.DistanceQuantileSampler(Distance<? super O> distance, double quantile, double sampling, boolean nozeros, RandomFactory rand)
Constructor.DistanceStatisticsWithClasses(Distance<? super O> distance, int numbins, boolean exact, boolean sampling)
Constructor.EvaluateRankingQuality(Distance<? super V> distance, int numbins)
Constructor.EvaluateRetrievalPerformance(Distance<? super O> distance, double sampling, RandomFactory random, boolean includeSelf, int maxk)
Constructor.RankingQualityHistogram(Distance<? super O> distance, int numbins)
Constructor. -
Uses of Distance in elki.application
Fields in elki.application declared as Distance Modifier and Type Field Description protected Distance<? super O>
AbstractDistanceBasedApplication. distance
Distance function to use.protected Distance<? super O>
AbstractDistanceBasedApplication.Par. distance
Distance function to useConstructors in elki.application with parameters of type Distance Constructor Description AbstractDistanceBasedApplication(InputStep inputstep, Distance<? super O> distance)
Constructor. -
Uses of Distance in elki.application.benchmark
Constructors in elki.application.benchmark with parameters of type Distance Constructor Description KNNBenchmark(InputStep inputstep, Distance<? super O> distance, int k, DatabaseConnection queries, double sampling, RandomFactory random)
Constructor.PrioritySearchBenchmark(InputStep inputstep, Distance<? super O> distance, int k, DatabaseConnection queries, double sampling, RandomFactory random)
Constructor.RangeQueryBenchmark(InputStep input, Distance<? super O> distance, double radius, double sampling, RandomFactory random)
Constructor.RangeQueryBenchmark(InputStep input, Distance<? super O> distance, DatabaseConnection queries, double sampling, RandomFactory random)
Constructor.ValidateApproximativeKNNIndex(InputStep input, Distance<? super O> distance, int k, DatabaseConnection queries, double sampling, boolean forcelinear, RandomFactory random, java.util.regex.Pattern pattern)
Constructor. -
Uses of Distance in elki.application.cache
Fields in elki.application.cache declared as Distance Modifier and Type Field Description private Distance<? super O>
CacheDoubleDistanceInOnDiskMatrix. distance
Distance function that is to be cached.private Distance<? super O>
CacheDoubleDistanceInOnDiskMatrix.Par. distance
Distance function that is to be cached.private Distance<? super O>
CacheDoubleDistanceKNNLists. distance
Distance function that is to be cached.private Distance<? super O>
CacheDoubleDistanceKNNLists.Par. distance
Distance function that is to be cached.private Distance<? super O>
CacheDoubleDistanceRangeQueries. distance
Distance function that is to be cached.private Distance<? super O>
CacheDoubleDistanceRangeQueries.Par. distance
Distance function that is to be cached.private Distance<? super O>
CacheFloatDistanceInOnDiskMatrix. distance
Distance function that is to be cached.private Distance<? super O>
CacheFloatDistanceInOnDiskMatrix.Par. distance
Distance function that is to be cached.private Distance<? super O>
PrecomputeDistancesAsciiApplication. distance
Distance function that is to be cached.private Distance<? super O>
PrecomputeDistancesAsciiApplication.Par. distance
Distance function that is to be cached.Constructors in elki.application.cache with parameters of type Distance Constructor Description CacheDoubleDistanceInOnDiskMatrix(Database database, Distance<? super O> distance, java.nio.file.Path out)
Constructor.CacheDoubleDistanceKNNLists(Database database, Distance<? super O> distance, int k, java.nio.file.Path out)
Constructor.CacheDoubleDistanceRangeQueries(Database database, Distance<? super O> distance, double radius, java.nio.file.Path out)
Constructor.CacheFloatDistanceInOnDiskMatrix(Database database, Distance<? super O> distance, java.nio.file.Path out)
Constructor.PrecomputeDistancesAsciiApplication(Database database, Distance<? super O> distance, java.nio.file.Path out)
Constructor. -
Uses of Distance in elki.application.greedyensemble
Constructors in elki.application.greedyensemble with parameters of type Distance Constructor Description ComputeKNNOutlierScores(InputStep inputstep, Distance<? super O> distance, IntGenerator krange, ByLabelOutlier bylabel, java.nio.file.Path outfile, ScalingFunction scaling, java.util.regex.Pattern disable, int ksquarestop, long timelimit)
Constructor. -
Uses of Distance in elki.application.statistics
Constructors in elki.application.statistics with parameters of type Distance Constructor Description EstimateIntrinsicDimensionality(InputStep inputstep, Distance<? super O> distance, IntrinsicDimensionalityEstimator<? super O> estimator, double krate, double samples)
Constructor.RangeQuerySelectivity(InputStep inputstep, Distance<? super V> distance, double radius, double sampling, RandomFactory random)
Constructor. -
Uses of Distance in elki.classification
Fields in elki.classification declared as Distance Modifier and Type Field Description protected Distance<? super O>
KNNClassifier. distance
Distance functionprotected Distance<? super O>
KNNClassifier.Par. distanceFunction
Distance functionMethods in elki.classification that return Distance Modifier and Type Method Description Distance<? super O>
KNNClassifier. getDistance()
Returns the distance.Constructors in elki.classification with parameters of type Distance Constructor Description KNNClassifier(Distance<? super O> distance, int k)
Constructor. -
Uses of Distance in elki.clustering
Fields in elki.clustering declared as Distance Modifier and Type Field Description private Distance<? super O>
CanopyPreClustering. distance
Distance function used.protected Distance<? super O>
CanopyPreClustering.Par. distance
The distance function to use.protected Distance<? super O>
CFSFDP. distance
Distance function used.protected Distance<? super O>
CFSFDP.Par. distance
The distance function to use.protected Distance<? super O>
Leader. distance
Distance function used.protected Distance<? super O>
Leader.Par. distance
The distance function to use.Constructors in elki.clustering with parameters of type Distance Constructor Description CanopyPreClustering(Distance<? super O> distance, double t1, double t2)
Constructor.CFSFDP(Distance<? super O> distance, double dc, int k)
Constructor.Leader(Distance<? super O> distance, double threshold)
Constructor. -
Uses of Distance in elki.clustering.affinitypropagation
Fields in elki.clustering.affinitypropagation declared as Distance Modifier and Type Field Description (package private) Distance<? super O>
DistanceBasedInitializationWithMedian. distance
Distance function.(package private) Distance<? super O>
DistanceBasedInitializationWithMedian.Par. distance
istance function.Constructors in elki.clustering.affinitypropagation with parameters of type Distance Constructor Description DistanceBasedInitializationWithMedian(Distance<? super O> distance, double quantile)
Constructor. -
Uses of Distance in elki.clustering.dbscan
Fields in elki.clustering.dbscan declared as Distance Modifier and Type Field Description protected Distance<? super O>
DBSCAN. distance
Distance function used.protected Distance<? super O>
DBSCAN.Par. distance
The distance function to use.protected Distance<? super V>
GriDBSCAN. distance
Distance function used.protected Distance<? super V>
GriDBSCAN.Instance. distance
Distance function used.protected Distance<? super O>
LSDBC. distance
Distance function used.protected Distance<? super O>
LSDBC.Par. distance
The distance function to use.Constructors in elki.clustering.dbscan with parameters of type Distance Constructor Description DBSCAN(Distance<? super O> distance, double epsilon, int minpts)
Constructor with parameters.GriDBSCAN(Distance<? super V> distance, double epsilon, int minpts, double gridwidth)
Constructor with parameters.Instance(Distance<? super V> distance, double epsilon, int minpts, double gridwidth)
Constructor.LSDBC(Distance<? super O> distance, int k, double alpha)
Constructor. -
Uses of Distance in elki.clustering.dbscan.predicates
Fields in elki.clustering.dbscan.predicates declared as Distance Modifier and Type Field Description protected Distance<? super O>
AbstractRangeQueryNeighborPredicate. distance
Distance function to use.protected Distance<? super O>
EpsilonNeighborPredicate. distance
Distance function to use(package private) Distance<O>
AbstractRangeQueryNeighborPredicate.Par. distfun
Distance function to useprotected Distance<O>
EpsilonNeighborPredicate.Par. distfun
Distance function to useConstructors in elki.clustering.dbscan.predicates with parameters of type Distance Constructor Description AbstractRangeQueryNeighborPredicate(double epsilon, Distance<? super O> distance)
Full constructor.EpsilonNeighborPredicate(double epsilon, Distance<? super O> distance)
Full constructor. -
Uses of Distance in elki.clustering.hierarchical
Fields in elki.clustering.hierarchical declared as Distance Modifier and Type Field Description protected Distance<? super O>
AbstractHDBSCAN. distance
Distance function used.protected Distance<? super O>
AbstractHDBSCAN.Par. distance
The distance function to use.protected Distance<? super O>
AGNES. distance
Distance function used.protected Distance<? super O>
AGNES.Par. distance
The distance function to use.protected Distance<? super O>
Anderberg.Par. distance
The distance function to use.protected Distance<? super O>
CLINK.Par. distance
The distance function to use.protected Distance<? super O>
HACAM. distance
Distance to useprotected Distance<? super O>
HACAM.Par. distance
The distance function to use.protected Distance<? super O>
MedoidLinkage. distance
The distance function to use.protected Distance<? super O>
MedoidLinkage.Par. distance
The distance function to use.protected Distance<? super O>
MiniMax. distance
Distance function used.protected Distance<? super O>
MiniMax.Par. distance
The distance function to use.protected Distance<? super O>
SLINK. distance
Distance function used.protected Distance<? super O>
SLINK.Par. distance
The distance function to use.Constructors in elki.clustering.hierarchical with parameters of type Distance Constructor Description AbstractHDBSCAN(Distance<? super O> distance, int minPts)
Constructor.AGNES(Distance<? super O> distance, Linkage linkage)
Constructor.Anderberg(Distance<? super O> distance, Linkage linkage)
Constructor.CLINK(Distance<? super O> distance)
Constructor.HACAM(Distance<? super O> distance, HACAM.Variant variant)
Constructor.HDBSCANLinearMemory(Distance<? super O> distance, int minPts)
Constructor.MedoidLinkage(Distance<? super O> distance)
Constructor.MiniMax(Distance<? super O> distance)
Constructor.MiniMaxAnderberg(Distance<? super O> distance)
Constructor.MiniMaxNNChain(Distance<? super O> distance)
Constructor.NNChain(Distance<? super O> distance, Linkage linkage)
Constructor.SLINK(Distance<? super O> distance)
Constructor.SLINKHDBSCANLinearMemory(Distance<? super O> distance, int minPts)
Constructor. -
Uses of Distance in elki.clustering.kcenter
Fields in elki.clustering.kcenter declared as Distance Modifier and Type Field Description (package private) Distance<? super O>
GreedyKCenter. distance
Distance function(package private) Distance<? super O>
GreedyKCenter.Par. distance
Distance function to useConstructors in elki.clustering.kcenter with parameters of type Distance Constructor Description GreedyKCenter(int k, Distance<? super O> distance, RandomFactory rand)
Constructor. -
Uses of Distance in elki.clustering.kmedoids
Fields in elki.clustering.kmedoids declared as Distance Modifier and Type Field Description protected Distance<? super O>
AlternatingKMedoids. distance
Distance function used.protected Distance<? super V>
AlternatingKMedoids.Par. distance
The distance function to use.protected Distance<? super O>
CLARANS. distance
Distance function used.protected Distance<? super V>
CLARANS.Par. distance
The distance function to use.protected Distance<? super O>
PAM. distance
Distance function used.protected Distance<? super O>
PAM.Par. distance
The distance function to use.Methods in elki.clustering.kmedoids that return Distance Modifier and Type Method Description Distance<? super V>
CLARA.CachedDistanceQuery. getDistance()
Constructors in elki.clustering.kmedoids with parameters of type Distance Constructor Description AlternatingKMedoids(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)
Constructor.CLARA(Distance<? super V> distance, int k, int maxiter, KMedoidsInitialization<V> initializer, int numsamples, double sampling, boolean keepmed, RandomFactory random)
Constructor.CLARANS(Distance<? super O> distance, int k, int numlocal, double maxneighbor, RandomFactory random)
Constructor.EagerPAM(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)
Constructor.FastCLARA(Distance<? super V> distance, int k, int maxiter, KMedoidsInitialization<V> initializer, double fasttol, int numsamples, double sampling, boolean keepmed, RandomFactory random)
Constructor.FastCLARANS(Distance<? super V> distance, int k, int numlocal, double maxneighbor, RandomFactory random)
Constructor.FasterCLARA(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer, int numsamples, double sampling, boolean keepmed, RandomFactory random)
Constructor.FasterPAM(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)
Constructor.FastPAM(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)
Constructor.FastPAM(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer, double fasttol)
Constructor.FastPAM1(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)
Constructor.PAM(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)
Constructor.ReynoldsPAM(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)
Constructor.SingleAssignmentKMedoids(Distance<? super O> distance, int k, KMedoidsInitialization<O> initializer)
Constructor. -
Uses of Distance in elki.clustering.optics
Fields in elki.clustering.optics declared as Distance Modifier and Type Field Description protected Distance<? super O>
AbstractOPTICS. distance
Distance function used.protected Distance<? super O>
AbstractOPTICS.Par. distance
The distance function to use.Constructors in elki.clustering.optics with parameters of type Distance Constructor Description AbstractOPTICS(Distance<? super O> distance, double epsilon, int minpts)
Constructor.OPTICSHeap(Distance<? super O> distance, double epsilon, int minpts)
Constructor.OPTICSList(Distance<? super O> distance, double epsilon, int minpts)
Constructor. -
Uses of Distance in elki.clustering.silhouette
Constructors in elki.clustering.silhouette with parameters of type Distance Constructor Description FasterMSC(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)
Constructor.FastMSC(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)
Constructor.PAMMEDSIL(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)
Constructor.PAMSIL(Distance<? super O> distance, int k, int maxiter, KMedoidsInitialization<O> initializer)
Constructor. -
Uses of Distance in elki.database.query
Fields in elki.database.query declared as Distance Modifier and Type Field Description private Distance<? super O>
QueryBuilder. distance
Distance to queryMethods in elki.database.query with parameters of type Distance Modifier and Type Method Description <O> DistanceQuery<O>
EmpiricalQueryOptimizer. getDistanceQuery(Relation<? extends O> relation, Distance<? super O> distance, int flags)
default <O> DistanceQuery<O>
QueryOptimizer. getDistanceQuery(Relation<? extends O> relation, Distance<? super O> distanceFunction, int flags)
Optimize a distance query for this relation.private <O> DistancePriorityIndex<O>
EmpiricalQueryOptimizer. makeCoverTree(Relation<? extends O> relation, Distance<? super O> distance, int leafsize)
private <O> DistancePriorityIndex<O>
EmpiricalQueryOptimizer. makeKDTree(Relation<? extends O> relation, Distance<? super O> distance, int k)
private <O> DistancePriorityIndex<O>
EmpiricalQueryOptimizer. makeMatrixIndex(Relation<? extends O> relation, Distance<? super O> distance)
private <O> DistancePriorityIndex<O>
EmpiricalQueryOptimizer. makeVPTree(Relation<? extends O> relation, Distance<? super O> distance, int leafsize)
Constructors in elki.database.query with parameters of type Distance Constructor Description QueryBuilder(Relation<O> relation, Distance<? super O> distance)
Constructor. -
Uses of Distance in elki.database.query.distance
Methods in elki.database.query.distance that return Distance Modifier and Type Method Description Distance<? super O>
DistanceQuery. getDistance()
Get the inner distance function. -
Uses of Distance in elki.distance
Classes in elki.distance with type parameters of type Distance Modifier and Type Class Description static class
AbstractIndexBasedDistance.Instance<O,I extends Index,F extends Distance<? super O>>
The actual instance bound to a particular database.Subinterfaces of Distance in elki.distance Modifier and Type Interface Description interface
DBIDDistance
Distance functions valid in a database context only (i.e. for DBIDs)interface
DBIDRangeDistance
Distance functions valid in a static database context only (i.e. for DBIDRanges) For any "distance" that cannot be computed for arbitrary objects, only those that exist in the database and referenced by their ID.interface
IndexBasedDistance<O>
Distance function relying on an index (such as preprocessed neighborhoods).interface
Norm<O>
Abstract interface for a mathematical norm.interface
NumberVectorDistance<O>
Base interface for the common case of distance functions defined on numerical vectors.interface
PrimitiveDistance<O>
Primitive distance function that is defined on some kind of object.interface
SpatialPrimitiveDistance<V extends SpatialComparable>
API for a spatial primitive distance function.interface
WeightedNumberVectorDistance<V>
Distance functions where each dimension is assigned a weight.Classes in elki.distance that implement Distance Modifier and Type Class Description class
AbstractDatabaseDistance<O>
Abstract super class for distance functions needing a database context.class
AbstractDBIDRangeDistance
Abstract base class for distance functions that rely on integer offsets within a consecutive range.class
AbstractIndexBasedDistance<O,F extends IndexFactory<O>>
Abstract super class for distance functions needing a database index.class
AbstractNumberVectorDistance
Abstract base class for the most common family of distance functions: defined on number vectors and returning double values.class
ArcCosineDistance
Arcus cosine distance function for feature vectors.class
ArcCosineUnitlengthDistance
Arcus cosine distance function for feature vectors.class
BrayCurtisDistance
Bray-Curtis distance function / Sørensen–Dice coefficient for continuous vector spaces (not only binary data).class
CanberraDistance
Canberra distance function, a variation of Manhattan distance.class
ClarkDistance
Clark distance function for vector spaces.class
CosineDistance
Cosine distance function for feature vectors.class
CosineUnitlengthDistance
Cosine distance function for unit length feature vectors.class
MahalanobisDistance
Mahalanobis quadratic form distance for feature vectors.class
MatrixWeightedQuadraticDistance
Matrix weighted quadratic distance, the squared form ofMahalanobisDistance
.class
RandomStableDistance
This is a dummy distance providing random values (obviously not metrical), useful mostly for unit tests and baseline evaluations: obviously this distance provides no benefit whatsoever.class
SharedNearestNeighborJaccardDistance<O>
SharedNearestNeighborJaccardDistance computes the Jaccard coefficient, which is a proper distance metric.class
SqrtCosineDistance
Cosine distance function for feature vectors using the square root.class
SqrtCosineUnitlengthDistance
Cosine distance function for unit length feature vectors using the square root.class
WeightedCanberraDistance
Weighted Canberra distance function, a variation of Manhattan distance.Fields in elki.distance declared as Distance Modifier and Type Field Description protected Distance<? super O>
AbstractDatabaseDistance.Instance. parent
Parent distanceprotected F
AbstractIndexBasedDistance.Instance. parent
Our parent distance functionMethods in elki.distance that return Distance Modifier and Type Method Description Distance<? super O>
AbstractDatabaseDistance.Instance. getDistance()
Constructors in elki.distance with parameters of type Distance Constructor Description Instance(Relation<O> relation, Distance<? super O> parent)
Constructor. -
Uses of Distance in elki.distance.adapter
Classes in elki.distance.adapter that implement Distance Modifier and Type Class Description class
AbstractSimilarityAdapter<O>
Adapter from a similarity function to a distance function.class
ArccosSimilarityAdapter<O>
Adapter from a normalized similarity function to a distance function usingarccos(sim)
.class
LinearSimilarityAdapter<O>
Adapter from a normalized similarity function to a distance function using1 - sim
.class
LnSimilarityAdapter<O>
Adapter from a normalized similarity function to a distance function using-log(sim)
.Constructors in elki.distance.adapter with parameters of type Distance Constructor Description Instance(Relation<O> database, Distance<? super O> parent, SimilarityQuery<? super O> similarityQuery)
Constructor.Instance(Relation<O> database, Distance<? super O> parent, SimilarityQuery<O> similarityQuery)
Constructor.Instance(Relation<O> database, Distance<? super O> parent, SimilarityQuery<? super O> similarityQuery)
Constructor.Instance(Relation<O> database, Distance<? super O> parent, SimilarityQuery<O> similarityQuery)
Constructor. -
Uses of Distance in elki.distance.colorhistogram
Classes in elki.distance.colorhistogram that implement Distance Modifier and Type Class Description class
HistogramIntersectionDistance
Intersection distance for color histograms.class
HSBHistogramQuadraticDistance
Distance function for HSB color histograms based on a quadratic form and color similarity.class
RGBHistogramQuadraticDistance
Distance function for RGB color histograms based on a quadratic form and color similarity. -
Uses of Distance in elki.distance.correlation
Classes in elki.distance.correlation that implement Distance Modifier and Type Class Description class
AbsolutePearsonCorrelationDistance
Absolute Pearson correlation distance function for feature vectors.class
AbsoluteUncenteredCorrelationDistance
Absolute uncentered correlation distance function for feature vectors.class
PearsonCorrelationDistance
Pearson correlation distance function for feature vectors.class
SquaredPearsonCorrelationDistance
Squared Pearson correlation distance function for feature vectors.class
SquaredUncenteredCorrelationDistance
Squared uncentered correlation distance function for feature vectors.class
UncenteredCorrelationDistance
Uncentered correlation distance.class
WeightedPearsonCorrelationDistance
Pearson correlation distance function for feature vectors.class
WeightedSquaredPearsonCorrelationDistance
Weighted squared Pearson correlation distance function for feature vectors. -
Uses of Distance in elki.distance.external
Classes in elki.distance.external that implement Distance Modifier and Type Class Description class
DiskCacheBasedDoubleDistance
Distance function that is based on double distances given by a distance matrix of an external binary matrix file.class
DiskCacheBasedFloatDistance
Distance function that is based on float distances given by a distance matrix of an external binary matrix file.class
FileBasedSparseDoubleDistance
Distance function that is based on double distances given by a distance matrix of an external ASCII file.class
FileBasedSparseFloatDistance
Distance function that is based on float distances given by a distance matrix of an external ASCII file. -
Uses of Distance in elki.distance.geo
Classes in elki.distance.geo that implement Distance Modifier and Type Class Description class
DimensionSelectingLatLngDistance
Distance function for 2D vectors in Latitude, Longitude form.class
LatLngDistance
Distance function for 2D vectors in Latitude, Longitude form.class
LngLatDistance
Distance function for 2D vectors in Longitude, Latitude form. -
Uses of Distance in elki.distance.histogram
Classes in elki.distance.histogram that implement Distance Modifier and Type Class Description class
HistogramMatchDistance
Distance function based on histogram matching, i.e., Manhattan distance on the cumulative density function.class
KolmogorovSmirnovDistance
Distance function based on the Kolmogorov-Smirnov goodness of fit test. -
Uses of Distance in elki.distance.minkowski
Classes in elki.distance.minkowski that implement Distance Modifier and Type Class Description class
EuclideanDistance
Euclidean distance forNumberVector
s.class
LPIntegerNormDistance
Lp-Norm forNumberVector
s, optimized version for integer values of p.class
LPNormDistance
Lp-Norm (Minkowski norms) are a family of distances forNumberVector
s.class
ManhattanDistance
Manhattan distance forNumberVector
s.class
MaximumDistance
Maximum distance forNumberVector
s.class
MinimumDistance
Minimum distance forNumberVector
s.class
SparseEuclideanDistance
Euclidean distance function, optimized forSparseNumberVector
s.class
SparseLPNormDistance
Lp-Norm, optimized forSparseNumberVector
s.class
SparseManhattanDistance
Manhattan distance, optimized forSparseNumberVector
s.class
SparseMaximumDistance
Maximum distance, optimized forSparseNumberVector
s.class
SparseSquaredEuclideanDistance
Squared Euclidean distance function, optimized forSparseNumberVector
s.class
SquaredEuclideanDistance
Squared Euclidean distance, optimized forSparseNumberVector
s.class
WeightedEuclideanDistance
Weighted Euclidean distance forNumberVector
s.class
WeightedLPNormDistance
Weighted version of the Minkowski Lp norm distance forNumberVector
.class
WeightedManhattanDistance
Weighted version of the Manhattan (L1) metric.class
WeightedMaximumDistance
Weighted version of the maximum distance function forNumberVector
s.class
WeightedSquaredEuclideanDistance
Weighted squared Euclidean distance forNumberVector
s. -
Uses of Distance in elki.distance.probabilistic
Classes in elki.distance.probabilistic that implement Distance Modifier and Type Class Description class
ChiDistance
χ distance function, symmetric version.class
ChiSquaredDistance
χ² distance function, symmetric version.class
FisherRaoDistance
Fisher-Rao riemannian metric for (discrete) probability distributions.class
HellingerDistance
Hellinger metric / affinity / kernel, Bhattacharyya coefficient, fidelity similarity, Matusita distance, Hellinger-Kakutani metric on a probability distribution.class
JeffreyDivergenceDistance
Jeffrey Divergence forNumberVector
s is a symmetric, smoothened version of theKullbackLeiblerDivergenceAsymmetricDistance
.class
JensenShannonDivergenceDistance
Jensen-Shannon Divergence forNumberVector
s is a symmetric, smoothened version of theKullbackLeiblerDivergenceAsymmetricDistance
.class
KullbackLeiblerDivergenceAsymmetricDistance
Kullback-Leibler divergence, also known as relative entropy, information deviation, or just KL-distance (albeit asymmetric).class
KullbackLeiblerDivergenceReverseAsymmetricDistance
Kullback-Leibler divergence, also known as relative entropy, information deviation or just KL-distance (albeit asymmetric).class
SqrtJensenShannonDivergenceDistance
The square root of Jensen-Shannon divergence is a metric.class
TriangularDiscriminationDistance
Triangular Discrimination has relatively tight upper and lower bounds to the Jensen-Shannon divergence, but is much less expensive.class
TriangularDistance
Triangular Distance has relatively tight upper and lower bounds to the (square root of the) Jensen-Shannon divergence, but is much less expensive. -
Uses of Distance in elki.distance.set
Classes in elki.distance.set that implement Distance Modifier and Type Class Description class
AbstractSetDistance<O>
Abstract base class for set distance functions.class
HammingDistance
Computes the Hamming distance of arbitrary vectors - i.e. counting, on how many places they differ.class
JaccardSimilarityDistance
A flexible extension of Jaccard similarity to non-binary vectors. -
Uses of Distance in elki.distance.strings
Classes in elki.distance.strings that implement Distance Modifier and Type Class Description class
LevenshteinDistance
Classic Levenshtein distance on strings.class
NormalizedLevenshteinDistance
Levenshtein distance on strings, normalized by string length. -
Uses of Distance in elki.distance.subspace
Subinterfaces of Distance in elki.distance.subspace Modifier and Type Interface Description interface
DimensionSelectingSubspaceDistance<O>
Interface for dimension selecting subspace distance functions.Classes in elki.distance.subspace that implement Distance Modifier and Type Class Description class
AbstractDimensionsSelectingDistance<V extends FeatureVector<?>>
Abstract base class for distances computed only in subspaces.class
OnedimensionalDistance
Distance function that computes the distance between feature vectors as the absolute difference of their values in a specified dimension only.class
SubspaceEuclideanDistance
Euclidean distance function betweenNumberVector
s only in specified dimensions.class
SubspaceLPNormDistance
Lp-Norm distance function betweenNumberVector
s only in specified dimensions.class
SubspaceManhattanDistance
Manhattan distance function betweenNumberVector
s only in specified dimensions.class
SubspaceMaximumDistance
Maximum distance function betweenNumberVector
s only in specified dimensions. -
Uses of Distance in elki.distance.timeseries
Classes in elki.distance.timeseries that implement Distance Modifier and Type Class Description class
AbstractEditDistance
Edit Distance for FeatureVectors.class
DerivativeDTWDistance
Derivative Dynamic Time Warping distance for numerical vectors.class
DTWDistance
Dynamic Time Warping distance (DTW) for numerical vectors.class
EDRDistance
Edit Distance on Real Sequence distance for numerical vectors.class
ERPDistance
Edit Distance With Real Penalty distance for numerical vectors.class
LCSSDistance
Longest Common Subsequence distance for numerical vectors. -
Uses of Distance in elki.evaluation.clustering.internal
Fields in elki.evaluation.clustering.internal declared as Distance Modifier and Type Field Description private Distance<? super O>
CIndex. distance
Distance function to use.private Distance<? super O>
CIndex.Par. distance
Distance function to use.private Distance<? super O>
DBCV. distance
Distance function to use.private Distance<? super O>
DBCV.Par. distance
Distance function to use.private Distance<? super O>
Silhouette. distance
Distance function to use.private Distance<? super O>
Silhouette.Par. distance
Distance function to use.Constructors in elki.evaluation.clustering.internal with parameters of type Distance Constructor Description CIndex(Distance<? super O> distance, NoiseHandling noiseOpt)
Constructor.DBCV(Distance<? super O> distance)
Constructor.Silhouette(Distance<? super O> distance, boolean mergenoise)
Constructor.Silhouette(Distance<? super O> distance, NoiseHandling noiseOption, boolean penalize)
Constructor. -
Uses of Distance in elki.evaluation.similaritymatrix
Fields in elki.evaluation.similaritymatrix declared as Distance Modifier and Type Field Description private Distance<? super O>
ComputeSimilarityMatrixImage. distance
The distance function to useprivate Distance<O>
ComputeSimilarityMatrixImage.Par. distance
The distance function to useConstructors in elki.evaluation.similaritymatrix with parameters of type Distance Constructor Description ComputeSimilarityMatrixImage(Distance<? super O> distance, ScalingFunction scaling, boolean skipzero)
Constructor. -
Uses of Distance in elki.index
Methods in elki.index with parameters of type Distance Modifier and Type Method Description DistanceQuery<O>
DistanceIndex. getDistanceQuery(Distance<? super O> distanceFunction)
Get a KNN query object for the given distance query and k. -
Uses of Distance in elki.index.distancematrix
Fields in elki.index.distancematrix declared as Distance Modifier and Type Field Description protected Distance<? super O>
PrecomputedDistanceMatrix. distance
Nested distance function.protected Distance<? super O>
PrecomputedDistanceMatrix.Factory. distance
Nested distance function.protected Distance<? super O>
PrecomputedDistanceMatrix.Factory.Par. distanceFunction
Nested distance function.Methods in elki.index.distancematrix that return Distance Modifier and Type Method Description Distance<? super O>
PrecomputedDistanceMatrix.PrecomputedDistanceQuery. getDistance()
Methods in elki.index.distancematrix with parameters of type Distance Modifier and Type Method Description DistanceQuery<O>
PrecomputedDistanceMatrix. getDistanceQuery(Distance<? super O> distanceFunction)
Constructors in elki.index.distancematrix with parameters of type Distance Constructor Description Factory(Distance<? super O> distance)
Constructor.PrecomputedDistanceMatrix(Relation<O> relation, DBIDRange range, Distance<? super O> distance)
Constructor. -
Uses of Distance in elki.index.idistance
Fields in elki.index.idistance declared as Distance Modifier and Type Field Description (package private) Distance<? super V>
InMemoryIDistanceIndex.Factory. distance
Distance function to use.(package private) Distance<? super V>
InMemoryIDistanceIndex.Factory.Par. distance
Distance function to use.Methods in elki.index.idistance that return Distance Modifier and Type Method Description private Distance<? super O>
InMemoryIDistanceIndex. getDistance()
Distance function.Constructors in elki.index.idistance with parameters of type Distance Constructor Description Factory(Distance<? super V> distance, KMedoidsInitialization<V> initialization, int k)
Constructor. -
Uses of Distance in elki.index.laesa
Fields in elki.index.laesa declared as Distance Modifier and Type Field Description (package private) Distance<? super O>
LAESA. distance
Distance function(package private) Distance<? super O>
LAESA.Factory. distance
Distance function(package private) Distance<? super O>
LAESA.Factory.Par. distance
Distance functionConstructors in elki.index.laesa with parameters of type Distance Constructor Description Factory(Distance<? super O> distance, int m, int k, RandomFactory rng)
Constructor.LAESA(Relation<O> relation, Distance<? super O> distance, int m, int k, RandomFactory rng)
Constructor. -
Uses of Distance in elki.index.lsh.hashfamilies
Methods in elki.index.lsh.hashfamilies with parameters of type Distance Modifier and Type Method Description boolean
CosineHashFunctionFamily. isCompatible(Distance<?> df)
boolean
EuclideanHashFunctionFamily. isCompatible(Distance<?> df)
boolean
LocalitySensitiveHashFunctionFamily. isCompatible(Distance<?> df)
Check whether the given distance function can be accelerated using this hash family.boolean
ManhattanHashFunctionFamily. isCompatible(Distance<?> df)
-
Uses of Distance in elki.index.preprocessed.knn
Fields in elki.index.preprocessed.knn declared as Distance Modifier and Type Field Description protected Distance<? super O>
AbstractMaterializeKNNPreprocessor. distance
The distance function to be used.protected Distance<? super O>
AbstractMaterializeKNNPreprocessor.Factory. distance
Hold the distance function to be used.protected Distance<? super O>
AbstractMaterializeKNNPreprocessor.Factory.Par. distance
Hold the distance function to be used.Methods in elki.index.preprocessed.knn that return Distance Modifier and Type Method Description Distance<? super O>
AbstractMaterializeKNNPreprocessor.Factory. getDistance()
Get the distance function.Constructors in elki.index.preprocessed.knn with parameters of type Distance Constructor Description AbstractMaterializeKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k)
Constructor.CachedDoubleDistanceKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k, java.nio.file.Path file)
Constructor.Factory(int k, Distance<? super O> distance)
Index factory.Factory(int k, Distance<? super O> distance, java.nio.file.Path filename)
Index factory.Factory(int k, Distance<? super O> distance)
Constructor.Factory(int k, Distance<? super O> distance)
Constructor.Factory(int k, Distance<? super O> distance)
Index factory.Factory(int k, Distance<? super O> distance)
Constructor.Factory(int k, Distance<? super O> distance, RandomFactory rnd, double delta, double rho, boolean noInitialNeighbors, int iterations)
Constructor.Factory(int k, Distance<? super O> distance, int partitions, RandomFactory rnd)
Constructor.Factory(int k, Distance<? super O> distance, double share, RandomFactory rnd)
Constructor.Factory(int k, Distance<? super V> distance, java.util.List<? extends SpatialSorter> curvegen, double window, int variants, RandomFactory random)
Constructor.Factory(int k, Distance<? super NumberVector> distance)
Constructor.KNNJoinMaterializeKNNPreprocessor(Relation<V> relation, Distance<? super V> distance, int k)
Constructor.MaterializeKNNAndRKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k)
Constructor.MaterializeKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k)
Constructor with preprocessing step.MetricalIndexApproximationMaterializeKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k)
ConstructorNNDescent(Relation<O> relation, Distance<? super O> distance, int k, RandomFactory rnd, double delta, double rho, boolean noInitialNeighbors, int iterations)
Constructor.PartitionApproximationMaterializeKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k, int partitions, RandomFactory rnd)
ConstructorRandomSampleKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k, double share, RandomFactory rnd)
Constructor.SpacefillingMaterializeKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k, java.util.List<? extends SpatialSorter> curvegen, double window, int variants, java.util.Random random)
Constructor.SpatialApproximationMaterializeKNNPreprocessor(Relation<O> relation, Distance<? super O> distance, int k)
Constructor -
Uses of Distance in elki.index.preprocessed.snn
Fields in elki.index.preprocessed.snn declared as Distance Modifier and Type Field Description protected Distance<O>
SharedNearestNeighborPreprocessor. distance
Hold the distance function to be used.protected Distance<O>
SharedNearestNeighborPreprocessor.Factory. distanceFunction
Hold the distance function to be used.protected Distance<O>
SharedNearestNeighborPreprocessor.Factory.Par. distanceFunction
Hold the distance function to be used.Constructors in elki.index.preprocessed.snn with parameters of type Distance Constructor Description Factory(int numberOfNeighbors, Distance<O> distance)
Constructor.SharedNearestNeighborPreprocessor(Relation<O> relation, int numberOfNeighbors, Distance<O> distance)
Constructor. -
Uses of Distance in elki.index.tree.metrical
Methods in elki.index.tree.metrical that return Distance Modifier and Type Method Description abstract Distance<? super O>
MetricalIndexTree. getDistance()
Returns the distance function of this metrical index. -
Uses of Distance in elki.index.tree.metrical.covertree
Fields in elki.index.tree.metrical.covertree declared as Distance Modifier and Type Field Description protected Distance<? super O>
AbstractCoverTree. distance
Holds the instance of the trees distance function.protected Distance<? super O>
AbstractCoverTree.Factory. distance
Holds the instance of the trees distance function.protected Distance<? super O>
AbstractCoverTree.Factory.Par. distance
Holds the instance of the trees distance function.Constructors in elki.index.tree.metrical.covertree with parameters of type Distance Constructor Description AbstractCoverTree(Relation<O> relation, Distance<? super O> distance, double expansion, int truncate)
Constructor.CoverTree(Relation<O> relation, Distance<? super O> distance, double expansion, int truncate)
Constructor.CoverTree(Relation<O> relation, Distance<? super O> distance, int truncate)
Constructor.Factory(Distance<? super O> distance, double expansion, int truncate)
Constructor.Factory(Distance<? super O> distance, double expansion, int truncate)
Constructor.Factory(Distance<? super O> distance, double expansion, int truncate)
Constructor.SimplifiedCoverTree(Relation<O> relation, Distance<? super O> distance, double expansion, int truncate)
Constructor. -
Uses of Distance in elki.index.tree.metrical.mtreevariants
Fields in elki.index.tree.metrical.mtreevariants declared as Distance Modifier and Type Field Description protected Distance<? super O>
MTreeSettings. distanceFunction
Holds the instance of the trees distance function.Methods in elki.index.tree.metrical.mtreevariants that return Distance Modifier and Type Method Description Distance<? super O>
AbstractMTree. getDistance()
-
Uses of Distance in elki.index.tree.metrical.vptree
Fields in elki.index.tree.metrical.vptree declared as Distance Modifier and Type Field Description (package private) Distance<? super O>
GNAT.Factory. distance
Distance Functionprotected Distance<? super O>
GNAT.Factory.Par. distance
Distance function(package private) Distance<? super O>
VPTree.Factory. distance
Distance Functionprotected Distance<? super O>
VPTree.Factory.Par. distance
Distance function(package private) Distance<? super O>
GNAT. distFunc
Distance Function to use(package private) Distance<? super O>
VPTree. distFunc
Distance Function to useConstructors in elki.index.tree.metrical.vptree with parameters of type Distance Constructor Description Factory(Distance<? super O> distFunc, RandomFactory random, int numberVantagePoints)
Constructor.Factory(Distance<? super O> distFunc, RandomFactory random, int sampleSize, int truncate)
Constructor.GNAT(Relation<O> relation, Distance<? super O> distance, RandomFactory random, int numberVPs)
Constructor.VPTree(Relation<O> relation, Distance<? super O> distance, int leafsize)
Constructor with default values, used by EmpiricalQueryOptimizerVPTree(Relation<O> relation, Distance<? super O> distance, RandomFactory random, int sampleSize, int truncate)
Constructor. -
Uses of Distance in elki.outlier
Fields in elki.outlier declared as Distance Modifier and Type Field Description protected Distance<? super V>
COP. distance
Distance function used.protected Distance<? super V>
COP.Par. distance
The distance function to use.protected Distance<? super O>
DWOF. distance
Distance function used.protected Distance<? super O>
DWOF.Par. distance
The distance function to use.protected Distance<? super O>
OPTICSOF. distance
Distance function used.protected Distance<? super O>
OPTICSOF.Par. distance
The distance function to use.protected Distance<? super V>
SimpleCOP. distance
Distance function used.protected Distance<? super V>
SimpleCOP.Par. distance
The distance function to use.Constructors in elki.outlier with parameters of type Distance Constructor Description COP(Distance<? super V> distance, int k, PCARunner pca, double expect, COP.DistanceDist dist, boolean models)
Constructor.DWOF(Distance<? super O> distance, int k, double delta)
Constructor.OPTICSOF(Distance<? super O> distance, int minpts)
Constructor with parameters.SimpleCOP(Distance<? super V> distance, int k, PCARunner pca, EigenPairFilter filter)
Constructor. -
Uses of Distance in elki.outlier.clustering
Fields in elki.outlier.clustering declared as Distance Modifier and Type Field Description protected Distance<? super O>
SilhouetteOutlierDetection. distance
Distance function used.protected Distance<? super O>
SilhouetteOutlierDetection.Par. distance
The distance function to use.Constructors in elki.outlier.clustering with parameters of type Distance Constructor Description SilhouetteOutlierDetection(Distance<? super O> distance, ClusteringAlgorithm<?> clusterer, NoiseHandling noiseOption)
Constructor. -
Uses of Distance in elki.outlier.distance
Fields in elki.outlier.distance declared as Distance Modifier and Type Field Description protected Distance<? super O>
AbstractDBOutlier. distance
Distance function used.protected Distance<? super O>
AbstractDBOutlier.Par. distance
The distance function to use.private Distance<? super O>
HilOut. distance
Distance function used.protected Distance<? super O>
KNNDD. distance
Distance function used.protected Distance<? super O>
KNNDD.Par. distance
The distance function to use.protected Distance<? super O>
KNNOutlier. distance
Distance function used.protected Distance<? super O>
KNNOutlier.Par. distance
The distance function to use.protected Distance<? super O>
KNNSOS. distance
Distance function used.protected Distance<? super O>
KNNSOS.Par. distance
The distance function to use.protected Distance<? super O>
KNNWeightOutlier. distance
Distance function used.protected Distance<? super O>
KNNWeightOutlier.Par. distance
The distance function to use.protected Distance<? super O>
LocalIsolationCoefficient. distance
Distance function used.protected Distance<? super O>
LocalIsolationCoefficient.Par. distance
The distance function to use.protected Distance<? super O>
ODIN. distance
Distance function used.protected Distance<? super O>
ODIN.Par. distance
The distance function to use.protected Distance<? super O>
SOS. distance
Distance function used.protected Distance<? super O>
SOS.Par. distance
The distance function to use.Constructors in elki.outlier.distance with parameters of type Distance Constructor Description AbstractDBOutlier(Distance<? super O> distance, double d)
Constructor with actual parameters.DBOutlierDetection(Distance<? super O> distance, double d, double p)
Constructor with actual parameters.DBOutlierScore(Distance<? super O> distance, double d)
Constructor with parameters.KNNDD(Distance<? super O> distance, int k)
Constructor for a single kNN query.KNNOutlier(Distance<? super O> distance, int k)
Constructor for a single kNN query.KNNSOS(Distance<? super O> distance, int k)
Constructor.KNNWeightOutlier(Distance<? super O> distance, int k)
Constructor with parameters.LocalIsolationCoefficient(Distance<? super O> distance, int k)
Constructor with parameters.ODIN(Distance<? super O> distance, int k)
Constructor.SOS(Distance<? super O> distance, double h)
Constructor. -
Uses of Distance in elki.outlier.distance.parallel
Fields in elki.outlier.distance.parallel declared as Distance Modifier and Type Field Description protected Distance<? super O>
ParallelKNNOutlier. distance
Distance function used.protected Distance<? super O>
ParallelKNNOutlier.Par. distance
The distance function to use.protected Distance<? super O>
ParallelKNNWeightOutlier. distance
Distance function used.protected Distance<? super O>
ParallelKNNWeightOutlier.Par. distance
The distance function to use.Constructors in elki.outlier.distance.parallel with parameters of type Distance Constructor Description ParallelKNNOutlier(Distance<? super O> distance, int k)
Constructor.ParallelKNNWeightOutlier(Distance<? super O> distance, int k)
Constructor. -
Uses of Distance in elki.outlier.intrinsic
Fields in elki.outlier.intrinsic declared as Distance Modifier and Type Field Description protected Distance<? super O>
IDOS. distance
Distance function used.protected Distance<? super O>
IDOS.Par. distance
The distance function to use.protected Distance<? super O>
ISOS. distance
Distance function used.protected Distance<? super O>
ISOS.Par. distance
The distance function to use.protected Distance<? super O>
LID. distance
Distance function used.protected Distance<? super O>
LID.Par. distance
The distance function to use.Constructors in elki.outlier.intrinsic with parameters of type Distance Constructor Description IDOS(Distance<? super O> distance, IntrinsicDimensionalityEstimator<? super O> estimator, int kc, int kr)
Constructor.ISOS(Distance<? super O> distance, int k, DistanceBasedIntrinsicDimensionalityEstimator estimator)
Constructor.LID(Distance<? super O> distance, int k, IntrinsicDimensionalityEstimator<? super O> estimator)
Constructor. -
Uses of Distance in elki.outlier.lof
Fields in elki.outlier.lof declared as Distance Modifier and Type Field Description protected Distance<? super O>
LoOP. comparisonDistance
Distance function for comparison set.protected Distance<O>
LoOP.Par. comparisonDistance
Preprocessor Step 2.protected Distance<? super O>
COF. distance
Distance function used.protected Distance<? super O>
COF.Par. distance
The distance function to use.protected Distance<? super O>
FlexibleLOF.Par. distance
The distance function to use.private Distance<? super O>
INFLO. distance
Distance function used.protected Distance<? super O>
INFLO.Par. distance
The distance function to use.protected Distance<? super O>
KDEOS. distance
Distance function used.protected Distance<? super O>
KDEOS.Par. distance
The distance function to use.protected Distance<? super O>
LDF. distance
Distance function used.protected Distance<? super O>
LDF.Par. distance
The distance function to use.protected Distance<? super O>
LDOF. distance
Distance function used.protected Distance<? super O>
LDOF.Par. distance
The distance function to use.private Distance<? super O>
LOCI. distance
Distance function used.protected Distance<? super O>
LOCI.Par. distance
The distance function to use.protected Distance<? super O>
LOF. distance
Distance function used.protected Distance<? super O>
LOF.Par. distance
The distance function to use.protected Distance<? super O>
SimpleKernelDensityLOF. distance
Distance function used.protected Distance<? super O>
SimpleKernelDensityLOF.Par. distance
The distance function to use.protected Distance<? super O>
SimplifiedLOF. distance
Distance function used.protected Distance<? super O>
SimplifiedLOF.Par. distance
The distance function to use.protected Distance<? super O>
VarianceOfVolume. distance
Distance function used.protected Distance<? super O>
VarianceOfVolume.Par. distance
The distance function to use.protected Distance<? super O>
FlexibleLOF.Par. reachabilityDistance
Reachability distance function.protected Distance<? super O>
FlexibleLOF. reachabilityDistance
Reachability distance function.protected Distance<O>
LoOP.Par. reachabilityDistance
Preprocessor Step 1.protected Distance<? super O>
LoOP. reachabilityDistance
Distance function for reachability.protected Distance<? super O>
FlexibleLOF. referenceDistance
Neighborhood distance function.Constructors in elki.outlier.lof with parameters of type Distance Constructor Description COF(Distance<? super O> distance, int k)
Constructor.FlexibleLOF(int krefer, int kreach, Distance<? super O> neighborhoodDistance, Distance<? super O> reachabilityDistance)
Constructor.INFLO(Distance<? super O> distance, double m, int k)
Constructor with parameters.KDEOS(Distance<? super O> distance, int kmin, int kmax, KernelDensityFunction kernel, double minBandwidth, double scale, int idim)
Constructor.LDF(int k, Distance<? super O> distance, KernelDensityFunction kernel, double h, double c)
Constructor.LDOF(Distance<? super O> distance, int k)
Constructor.LOCI(Distance<? super O> distance, double rmax, int nmin, double alpha)
Constructor.LOF(int k, Distance<? super O> distance)
Constructor.LoOP(int kreach, int kcomp, Distance<? super O> reachabilityDistance, Distance<? super O> comparisonDistance, double lambda)
Constructor with parameters.OnlineLOF(int krefer, int kreach, Distance<? super O> neighborhoodDistance, Distance<? super O> reachabilityDistance)
Constructor.SimpleKernelDensityLOF(int k, Distance<? super O> distance, KernelDensityFunction kernel)
Constructor.SimplifiedLOF(Distance<? super O> distance, int k)
Constructor.VarianceOfVolume(int k, Distance<? super O> distance)
Constructor. -
Uses of Distance in elki.outlier.lof.parallel
Fields in elki.outlier.lof.parallel declared as Distance Modifier and Type Field Description protected Distance<? super O>
ParallelLOF. distance
Distance function used.protected Distance<? super O>
ParallelLOF.Par. distance
The distance function to use.protected Distance<? super O>
ParallelSimplifiedLOF. distance
Distance function used.protected Distance<? super O>
ParallelSimplifiedLOF.Par. distance
The distance function to use.Constructors in elki.outlier.lof.parallel with parameters of type Distance Constructor Description ParallelLOF(Distance<? super O> distance, int k)
Constructor.ParallelSimplifiedLOF(Distance<? super O> distance, int k)
Constructor. -
Uses of Distance in elki.outlier.spatial
Fields in elki.outlier.spatial declared as Distance Modifier and Type Field Description protected Distance<? super V>
CTLuGLSBackwardSearchAlgorithm. distance
Distance function used.protected Distance<? super V>
CTLuGLSBackwardSearchAlgorithm.Par. distance
The distance function to use.private Distance<? super O>
CTLuRandomWalkEC. distance
Distance function used.protected Distance<? super O>
CTLuRandomWalkEC.Par. distance
The distance function to use.private Distance<O>
AbstractDistanceBasedSpatialOutlier. nonSpatialDistance
The distance function to useMethods in elki.outlier.spatial that return Distance Modifier and Type Method Description protected Distance<O>
AbstractDistanceBasedSpatialOutlier. getNonSpatialDistance()
Get the non-spatial relationConstructors in elki.outlier.spatial with parameters of type Distance Constructor Description AbstractDistanceBasedSpatialOutlier(NeighborSetPredicate.Factory<N> npredf, Distance<O> nonSpatialDistance)
Constructor.CTLuGLSBackwardSearchAlgorithm(Distance<? super V> distance, int k, double alpha)
Constructor.CTLuRandomWalkEC(Distance<? super O> distance, double alpha, double c, int k)
Constructor. -
Uses of Distance in elki.outlier.spatial.neighborhood
Fields in elki.outlier.spatial.neighborhood declared as Distance Modifier and Type Field Description private Distance<? super O>
PrecomputedKNearestNeighborNeighborhood.Factory. distance
distance function to use(package private) Distance<? super O>
PrecomputedKNearestNeighborNeighborhood.Factory.Par. distFunc
Distance functionConstructors in elki.outlier.spatial.neighborhood with parameters of type Distance Constructor Description Factory(int k, Distance<? super O> distance)
Factory Constructor -
Uses of Distance in elki.projection
Fields in elki.projection declared as Distance Modifier and Type Field Description protected Distance<? super O>
GaussianAffinityMatrixBuilder. distance
Input distance function.protected Distance<? super O>
GaussianAffinityMatrixBuilder.Par. distance
The distance function to use.protected Distance<? super O>
PerplexityAffinityMatrixBuilder. distance
Input distance function.protected Distance<? super O>
PerplexityAffinityMatrixBuilder.Par. distance
The distance function to use.Constructors in elki.projection with parameters of type Distance Constructor Description GaussianAffinityMatrixBuilder(Distance<? super O> distance, double sigma)
Constructor.IntrinsicNearestNeighborAffinityMatrixBuilder(Distance<? super O> distance, double perplexity, DistanceBasedIntrinsicDimensionalityEstimator estimator)
Constructor.NearestNeighborAffinityMatrixBuilder(Distance<? super O> distance, double perplexity)
Constructor.NearestNeighborAffinityMatrixBuilder(Distance<? super O> distance, double perplexity, int neighbors)
Constructor.PerplexityAffinityMatrixBuilder(Distance<? super O> distance, double perplexity)
Constructor. -
Uses of Distance in elki.similarity
Classes in elki.similarity that implement Distance Modifier and Type Class Description class
Kulczynski1Similarity
Kulczynski similarity 1. -
Uses of Distance in elki.similarity.cluster
Subinterfaces of Distance in elki.similarity.cluster Modifier and Type Interface Description interface
ClusteringDistanceSimilarity
Distance and similarity measure for clusterings.Classes in elki.similarity.cluster that implement Distance Modifier and Type Class Description class
ClusteringAdjustedRandIndexSimilarity
Measure the similarity of clusters via the Adjusted Rand Index.class
ClusteringBCubedF1Similarity
Measure the similarity of clusters via the BCubed F1 Index.class
ClusteringFowlkesMallowsSimilarity
Measure the similarity of clusters via the Fowlkes-Mallows Index.class
ClusteringRandIndexSimilarity
Measure the similarity of clusters via the Rand Index.class
ClusterIntersectionSimilarity
Measure the similarity of clusters via the intersection size.class
ClusterJaccardSimilarity
Measure the similarity of clusters via the Jaccard coefficient. -
Uses of Distance in elki.similarity.kernel
Classes in elki.similarity.kernel that implement Distance Modifier and Type Class Description class
LinearKernel
Linear Kernel function that computes a similarity between the two feature vectors x and y defined by \(x^T\cdot y\).class
PolynomialKernel
Polynomial Kernel function that computes a similarity between the two feature vectors x and y defined by \((x^T\cdot y+b)^{\text{degree}}\). -
Uses of Distance in tutorial.clustering
Fields in tutorial.clustering declared as Distance Modifier and Type Field Description protected Distance<? super O>
CFSFDP. distance
Distance function used.protected Distance<? super O>
CFSFDP.Par. distance
The distance function to use.(package private) Distance<? super O>
NaiveAgglomerativeHierarchicalClustering1. distance
Distance function used.protected Distance<? super O>
NaiveAgglomerativeHierarchicalClustering1.Par. distance
The distance function to use.(package private) Distance<? super O>
NaiveAgglomerativeHierarchicalClustering2. distance
Distance function used.protected Distance<? super O>
NaiveAgglomerativeHierarchicalClustering2.Par. distance
The distance function to use.(package private) Distance<? super O>
NaiveAgglomerativeHierarchicalClustering3. distance
Distance function used.protected Distance<? super O>
NaiveAgglomerativeHierarchicalClustering3.Par. distance
The distance function to use.(package private) Distance<? super O>
NaiveAgglomerativeHierarchicalClustering4. distance
Distance function used.protected Distance<? super O>
NaiveAgglomerativeHierarchicalClustering4.Par. distance
The distance function to use.Constructors in tutorial.clustering with parameters of type Distance Constructor Description CFSFDP(Distance<? super O> distance, double dc, int k)
Constructor.NaiveAgglomerativeHierarchicalClustering1(Distance<? super O> distance, int numclusters)
Constructor.NaiveAgglomerativeHierarchicalClustering2(Distance<? super O> distance, int numclusters)
Constructor.NaiveAgglomerativeHierarchicalClustering3(Distance<? super O> distance, int numclusters, NaiveAgglomerativeHierarchicalClustering3.Linkage linkage)
Constructor.NaiveAgglomerativeHierarchicalClustering4(Distance<? super O> distance, NaiveAgglomerativeHierarchicalClustering4.Linkage linkage)
Constructor. -
Uses of Distance in tutorial.distancefunction
Classes in tutorial.distancefunction that implement Distance Modifier and Type Class Description class
MultiLPNorm
Tutorial example Minowski-distance variation with different exponents for different dimensions for ELKI.class
TutorialDistance
Tutorial distance function example for ELKI. -
Uses of Distance in tutorial.outlier
Fields in tutorial.outlier declared as Distance Modifier and Type Field Description protected Distance<? super O>
DistanceStddevOutlier. distance
Distance function used.protected Distance<? super O>
DistanceStddevOutlier.Par. distance
The distance function to use.(package private) Distance<? super O>
ODIN. distance
Distance function used.protected Distance<? super O>
ODIN.Par. distance
The distance function to use.Constructors in tutorial.outlier with parameters of type Distance Constructor Description DistanceStddevOutlier(Distance<? super O> distance, int k)
Constructor.ODIN(Distance<? super O> distance, int k)
Constructor.
-