Uses of Interface
de.lmu.ifi.dbs.elki.data.NumberVector

Packages that use NumberVector

de.lmu.ifi.dbs.elki.algorithm	Algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.clustering	Clustering algorithms Clustering algorithms are supposed to implement the Algorithm-Interface.
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation	Correlation clustering algorithms
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace	Axis-parallel subspace clustering algorithms The clustering algorithms in this package are instances of both, projected clustering algorithms or subspace clustering algorithms according to the classical but somewhat obsolete classification schema of clustering algorithms for axis-parallel subspaces.
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique	Helper classes for the CLIQUE algorithm.
de.lmu.ifi.dbs.elki.algorithm.outlier	Outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.outlier.meta	Meta outlier detection algorithms: external scores, score rescaling.
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial	Spatial outlier detection algorithms
de.lmu.ifi.dbs.elki.algorithm.statistics	Statistical analysis algorithms The algorithms in this package perform statistical analysis of the data (e.g. compute distributions, distance distributions etc.)
de.lmu.ifi.dbs.elki.application.visualization	Visualization applications in ELKI.
de.lmu.ifi.dbs.elki.data	Basic classes for different data types, database object types and label types.
de.lmu.ifi.dbs.elki.data.model	Cluster models classes for various algorithms.
de.lmu.ifi.dbs.elki.data.type	Data type information, also used for type restrictions.
de.lmu.ifi.dbs.elki.datasource.filter	Data filtering, in particular for normalization and projection.
de.lmu.ifi.dbs.elki.datasource.parser	Parsers for different file formats and data types.
de.lmu.ifi.dbs.elki.distance.distancefunction	Distance functions for use within ELKI.
de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram	Distance functions using correlations.
de.lmu.ifi.dbs.elki.distance.distancefunction.correlation	Distance functions using correlations.
de.lmu.ifi.dbs.elki.distance.distancefunction.geo	Geographic (earth) distance functions.
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace	Distance functions based on subspaces.
de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries	Distance functions designed for time series.
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel	Kernel functions.
de.lmu.ifi.dbs.elki.index.preprocessed	Index structure based on preprocessors
de.lmu.ifi.dbs.elki.index.preprocessed.knn	Indexes providing KNN and rKNN data.
de.lmu.ifi.dbs.elki.index.preprocessed.localpca	Index using a preprocessed local PCA.
de.lmu.ifi.dbs.elki.index.preprocessed.preference	Indexes storing preference vectors.
de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj	Index using a preprocessed local subspaces.
de.lmu.ifi.dbs.elki.index.tree.spatial	Tree-based index structures for spatial indexing.
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants	R*-Tree and variants.
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu	DeLiCluTree
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar	RStarTree
de.lmu.ifi.dbs.elki.math	Mathematical operations and utilities used throughout the framework.
de.lmu.ifi.dbs.elki.math.linearalgebra	Linear Algebra package provides classes and computational methods for operations on matrices.
de.lmu.ifi.dbs.elki.math.linearalgebra.pca	Principal Component Analysis (PCA) and Eigenvector processing.
de.lmu.ifi.dbs.elki.math.spacefillingcurves	Space filling curves.
de.lmu.ifi.dbs.elki.utilities	Utility and helper classes - commonly used data structures, output formatting, exceptions, ...
de.lmu.ifi.dbs.elki.utilities.referencepoints	Package containing strategies to obtain reference points Shared code for various algorithms that use reference points.
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.scales	Scales handling for plotting.
de.lmu.ifi.dbs.elki.visualization.svg	Base SVG functionality (generation, markers, thumbnails, export, ...).
de.lmu.ifi.dbs.elki.visualization.visualizers	Visualizers for various results
de.lmu.ifi.dbs.elki.visualization.visualizers.vis1d	Visualizers based on 1D projections.
de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d	Visualizers based on 2D projections.

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

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

class	DependencyDerivator<V extends NumberVector<V,?>,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<V,?>,D extends Distance<D>> Parameterization class.
class	DummyAlgorithm<O extends NumberVector<?,?>> Dummy Algorithm, which just iterates over all points once, doing a 10NN query each.
class	KNNJoin<V extends NumberVector<V,?>,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<V,?>,D extends Distance<D>,N extends SpatialNode<N,E>,E extends SpatialEntry> Parameterization class.

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

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

class	AbstractProjectedClustering<R extends Clustering<Model>,V extends NumberVector<V,?>> Abstract superclass for projected clustering algorithms, like PROCLUS and ORCLUS.
class	AbstractProjectedDBSCAN<R extends Clustering<Model>,V extends NumberVector<V,?>> Provides an abstract algorithm requiring a VarianceAnalysisPreprocessor.
static class	AbstractProjectedDBSCAN.Parameterizer<V extends NumberVector<V,?>,D extends Distance<D>> Parameterization class.
class	DeLiClu<NV extends NumberVector<NV,?>,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<NV,?>,D extends Distance<D>> Parameterization class.
class	EM<V extends NumberVector<V,?>> Provides the EM algorithm (clustering by expectation maximization).
static class	EM.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	KMeans<V extends NumberVector<V,?>,D extends Distance<D>> Provides the k-means algorithm.
static class	KMeans.Parameterizer<V extends NumberVector<V,?>,D extends Distance<D>> Parameterization class.

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

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

class	COPAC<V extends NumberVector<V,?>,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<V,?>,D extends Distance<D>> Parameterization class.
class	ERiC<V extends NumberVector<V,?>> Performs correlation clustering on the data partitioned according to local correlation dimensionality and builds a hierarchy of correlation clusters that allows multiple inheritance from the clustering result.
static class	ERiC.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	FourC<V extends NumberVector<V,?>> 4C identifies local subgroups of data objects sharing a uniform correlation.
static class	FourC.Parameterizer<O extends NumberVector<O,?>> Parameterization class.
class	HiCO<V extends NumberVector<V,?>> Implementation of the HiCO algorithm, an algorithm for detecting hierarchies of correlation clusters.
static class	HiCO.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	ORCLUS<V extends NumberVector<V,?>> ORCLUS provides the ORCLUS algorithm, an algorithm to find clusters in high dimensional spaces.
static class	ORCLUS.Parameterizer<V extends NumberVector<V,?>> Parameterization class.

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

(package private) V

ORCLUS.ORCLUSCluster.centroid The centroid of this cluster.

Uses of NumberVector in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace

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

class	CLIQUE<V extends NumberVector<V,?>> Implementation of the CLIQUE algorithm, a grid-based algorithm to identify dense clusters in subspaces of maximum dimensionality.
static class	CLIQUE.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	DiSH<V extends NumberVector<V,?>> Algorithm for detecting subspace hierarchies.
static class	DiSH.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	HiSC<V extends NumberVector<V,?>> Implementation of the HiSC algorithm, an algorithm for detecting hierarchies of subspace clusters.
static class	HiSC.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	PreDeCon<V extends NumberVector<V,?>> PreDeCon computes clusters of subspace preference weighted connected points.
static class	PreDeCon.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	PROCLUS<V extends NumberVector<V,?>> Provides the PROCLUS algorithm, an algorithm to find subspace clusters in high dimensional spaces.
static class	PROCLUS.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	SUBCLU<V extends NumberVector<V,?>> Implementation of the SUBCLU algorithm, an algorithm to detect arbitrarily shaped and positioned clusters in subspaces.
static class	SUBCLU.Parameterizer<V extends NumberVector<V,?>> Parameterization class.

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

(package private) V

PROCLUS.PROCLUSCluster.centroid The centroids of this cluster along each dimension.

Uses of NumberVector in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique with type parameters of type NumberVector

class	CLIQUESubspace<V extends NumberVector<V,?>> Represents a subspace of the original data space in the CLIQUE algorithm.
class	CLIQUEUnit<V extends NumberVector<V,?>> Represents a unit in the CLIQUE algorithm.

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

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

class	ABOD<V extends NumberVector<V,?>> Angle-Based Outlier Detection Outlier detection using variance analysis on angles, especially for high dimensional data sets.
static class	ABOD.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	AbstractAggarwalYuOutlier<V extends NumberVector<?,?>> Abstract base class for the sparse-grid-cell based outlier detection of Aggarwal and Yu.
class	AggarwalYuEvolutionary<V extends NumberVector<?,?>> EAFOD provides the evolutionary outlier detection algorithm, an algorithm to detect outliers for high dimensional data.
static class	AggarwalYuEvolutionary.Parameterizer<V extends NumberVector<?,?>> Parameterization class.
class	AggarwalYuNaive<V extends NumberVector<?,?>> BruteForce provides a naive brute force algorithm in which all k-subsets of dimensions are examined and calculates the sparsity coefficient to find outliers.
static class	AggarwalYuNaive.Parameterizer<V extends NumberVector<?,?>> Parameterization class.
class	EMOutlier<V extends NumberVector<V,?>> outlier detection algorithm using EM Clustering.
static class	EMOutlier.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	GaussianModel<V extends NumberVector<V,?>> Outlier have smallest GMOD_PROB: the outlier scores is the probability density of the assumed distribution.
static class	GaussianModel.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	GaussianUniformMixture<V extends NumberVector<V,?>> Outlier detection algorithm using a mixture model approach.
static class	GaussianUniformMixture.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	ReferenceBasedOutlierDetection<V extends NumberVector<?,?>,D extends NumberDistance<D,?>> provides the Reference-Based Outlier Detection algorithm, an algorithm that computes kNN distances approximately, using reference points.
static class	ReferenceBasedOutlierDetection.Parameterizer<V extends NumberVector<?,?>,D extends NumberDistance<D,?>> Parameterization class.
class	SOD<V extends NumberVector<V,?>>
static class	SOD.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
static class	SOD.SODModel<O extends NumberVector<O,?>>

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

private O

SOD.SODModel.center

Uses of NumberVector in de.lmu.ifi.dbs.elki.algorithm.outlier.meta

Method parameters in de.lmu.ifi.dbs.elki.algorithm.outlier.meta with type arguments of type NumberVector

OutlierResult

FeatureBagging.run(Relation<NumberVector<?,?>> relation) Run the algorithm on a data set.

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

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

class	CTLuGLSBackwardSearchAlgorithm<V extends NumberVector<?,?>,D extends NumberDistance<D,?>> GLS-Backward Search is a statistical approach to detecting spatial outliers.
static class	CTLuGLSBackwardSearchAlgorithm.Parameterizer<V extends NumberVector<?,?>,D extends NumberDistance<D,?>> Parameterization class
class	CTLuMeanMultipleAttributes<N,O extends NumberVector<?,?>> Mean Approach is used to discover spatial outliers with multiple attributes.
static class	CTLuMeanMultipleAttributes.Parameterizer<N,O extends NumberVector<?,?>> Parameterization class.
class	CTLuMedianMultipleAttributes<N,O extends NumberVector<?,?>> Median Approach is used to discover spatial outliers with multiple attributes.
static class	CTLuMedianMultipleAttributes.Parameterizer<N,O extends NumberVector<?,?>> Parameterization class.

Method parameters in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial with type arguments of type NumberVector

OutlierResult	TrimmedMeanApproach.run(Database database, Relation<N> nrel, Relation<? extends NumberVector<?,?>> relation) Run the algorithm
OutlierResult	CTLuZTestOutlier.run(Database database, Relation<N> nrel, Relation<? extends NumberVector<?,?>> relation) Main method
OutlierResult	CTLuRandomWalkEC.run(Relation<N> spatial, Relation<? extends NumberVector<?,?>> relation) Run the algorithm
OutlierResult	CTLuScatterplotOutlier.run(Relation<N> nrel, Relation<? extends NumberVector<?,?>> relation) Main method
OutlierResult	CTLuMoranScatterplotOutlier.run(Relation<N> nrel, Relation<? extends NumberVector<?,?>> relation) Main method
OutlierResult	CTLuMedianAlgorithm.run(Relation<N> nrel, Relation<? extends NumberVector<?,?>> relation) Main method
OutlierResult	CTLuGLSBackwardSearchAlgorithm.run(Relation<V> relationx, Relation<? extends NumberVector<?,?>> relationy) Run the algorithm
private Pair<DBID,Double>	CTLuGLSBackwardSearchAlgorithm.singleIteration(Relation<V> relationx, Relation<? extends NumberVector<?,?>> relationy) Run a single iteration of the GLS-SOD modeling step

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

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

class	EvaluateRankingQuality<V extends NumberVector<V,?>,D extends NumberDistance<D,?>> Evaluate a distance function with respect to kNN queries.
static class	EvaluateRankingQuality.Parameterizer<V extends NumberVector<V,?>,D extends NumberDistance<D,?>> Parameterization class.

Uses of NumberVector in de.lmu.ifi.dbs.elki.application.visualization

Classes in de.lmu.ifi.dbs.elki.application.visualization with type parameters of type NumberVector

class	KNNExplorer<O extends NumberVector<?,?>,D extends NumberDistance<D,?>> User application to explore the k Nearest Neighbors for a given data set and distance function.
static class	KNNExplorer.Parameterizer<O extends NumberVector<?,?>,D extends NumberDistance<D,?>> Parameterization class.

Uses of NumberVector in de.lmu.ifi.dbs.elki.data

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

interface

NumberVector<V extends NumberVector<? extends V,N>,N extends Number> Interface NumberVector defines the methods that should be implemented by any Object that is element of a real vector space of type N.

Subinterfaces of NumberVector in de.lmu.ifi.dbs.elki.data

interface

SparseNumberVector<V extends SparseNumberVector<V,N>,N extends Number> Combines the SparseFeatureVector and NumberVector

Classes in de.lmu.ifi.dbs.elki.data that implement NumberVector

class	AbstractNumberVector<V extends AbstractNumberVector<? extends V,N>,N extends Number> AbstractNumberVector is an abstract implementation of FeatureVector.
class	BitVector Provides a BitVector wrapping a BitSet.
class	DoubleVector A DoubleVector is to store real values approximately as double values.
class	FloatVector A FloatVector is to store real values approximately as float values.
class	IntegerVector An IntegerVector is to store integer values.
class	OneDimensionalDoubleVector Specialized class implementing a one-dimensional double vector without using an array.
class	ParameterizationFunction A parameterization function describes all lines in a d-dimensional feature space intersecting in one point p.
class	SparseFloatVector A SparseFloatVector is to store real values approximately as float values.

Methods in de.lmu.ifi.dbs.elki.data with type parameters of type NumberVector

static <V extends NumberVector<?,?>> DoubleMinMax	VectorUtil.getRangeDouble(V vec) Return the range across all dimensions.
static <V extends NumberVector<V,?>> V	VectorUtil.randomVector(V template) Produce a new vector based on random numbers in [0:1] of the same type and dimensionality as the given vector.
static <V extends NumberVector<V,?>> V	VectorUtil.randomVector(V template, Random r) Produce a new vector based on random numbers in [0:1] of the same type and dimensionality as the given vector.

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

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

class

CorrelationAnalysisSolution<V extends NumberVector<V,?>> A solution of correlation analysis is a matrix of equations describing the dependencies.

Uses of NumberVector in de.lmu.ifi.dbs.elki.data.type

Fields in de.lmu.ifi.dbs.elki.data.type with type parameters of type NumberVector

static VectorFieldTypeInformation<NumberVector<?,?>>

TypeUtil.NUMBER_VECTOR_FIELD Input type for algorithms that require number vector fields.

Uses of NumberVector in de.lmu.ifi.dbs.elki.datasource.filter

Classes in de.lmu.ifi.dbs.elki.datasource.filter with type parameters of type NumberVector

static class	AbstractFeatureSelectionFilter.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
static class	AbstractRandomFeatureSelectionFilter.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	AttributeWiseErfNormalization<O extends NumberVector<O,?>> Attribute-wise Normalization using the error function.
class	AttributeWiseMinMaxNormalization<V extends NumberVector<V,?>> Class to perform and undo a normalization on real vectors with respect to given minimum and maximum in each dimension.
static class	AttributeWiseMinMaxNormalization.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	AttributeWiseVarianceNormalization<V extends NumberVector<V,?>> Class to perform and undo a normalization on real vectors with respect to given mean and standard deviation in each dimension.
static class	AttributeWiseVarianceNormalization.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	SplitNumberVectorFilter<V extends NumberVector<V,?>> Split an existing column into two types.
static class	SplitNumberVectorFilter.Parameterizer<V extends NumberVector<V,?>> Parameterization class.

Uses of NumberVector in de.lmu.ifi.dbs.elki.datasource.parser

Classes in de.lmu.ifi.dbs.elki.datasource.parser with type parameters of type NumberVector

class	NumberVectorLabelParser<V extends NumberVector<?,?>> Provides a parser for parsing one point per line, attributes separated by whitespace.
static class	NumberVectorLabelParser.Parameterizer<V extends NumberVector<?,?>> Parameterization class.

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

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

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.
class	LocallyWeightedDistanceFunction<V extends NumberVector<?,?>> Provides a locally weighted distance function.
static class	LocallyWeightedDistanceFunction.Instance<V extends NumberVector<?,?>> Instance of this distance for a particular database.
static class	LocallyWeightedDistanceFunction.Parameterizer<V extends NumberVector<?,?>> Parameterization class.

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

<T extends NumberVector<?,?>> PrimitiveDistanceQuery<T,DoubleDistance>	AbstractCosineDistanceFunction.instantiate(Relation<T> relation)
<T extends NumberVector<?,?>> SpatialPrimitiveDistanceQuery<T,DoubleDistance>	SquaredEuclideanDistanceFunction.instantiate(Relation<T> relation)
<T extends NumberVector<?,?>> SpatialPrimitiveDistanceQuery<T,DoubleDistance>	ManhattanDistanceFunction.instantiate(Relation<T> relation)
<T extends NumberVector<?,?>> SpatialPrimitiveDistanceQuery<T,DoubleDistance>	EuclideanDistanceFunction.instantiate(Relation<T> relation)
<T extends NumberVector<?,?>> SpatialDistanceQuery<T,DoubleDistance>	MaximumDistanceFunction.instantiate(Relation<T> relation)
<T extends NumberVector<?,?>> SpatialPrimitiveDistanceQuery<T,DoubleDistance>	MinimumDistanceFunction.instantiate(Relation<T> relation)

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction that return types with arguments of type NumberVector

SimpleTypeInformation<? super NumberVector<?,?>>	AbstractVectorDoubleDistanceFunction.getInputTypeRestriction()
VectorFieldTypeInformation<? super NumberVector<?,?>>	WeightedDistanceFunction.getInputTypeRestriction()

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

protected double	AbstractCosineDistanceFunction.angle(NumberVector<?,?> v1, NumberVector<?,?> v2) Compute the angle between two vectors.
protected double	AbstractCosineDistanceFunction.angle(NumberVector<?,?> v1, NumberVector<?,?> v2) Compute the angle between two vectors.
DoubleDistance	AbstractVectorDoubleDistanceFunction.distance(NumberVector<?,?> o1, NumberVector<?,?> o2)
DoubleDistance	AbstractVectorDoubleDistanceFunction.distance(NumberVector<?,?> o1, NumberVector<?,?> o2)
double	SquaredEuclideanDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the squared Euclidean distance between the given two vectors.
double	SquaredEuclideanDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the squared Euclidean distance between the given two vectors.
double	ManhattanDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Compute the Manhattan distance
double	ManhattanDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Compute the Manhattan distance
double	EuclideanDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the Euclidean distance between the given two vectors.
double	EuclideanDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the Euclidean distance between the given two vectors.
double	MaximumDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2)
double	MaximumDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2)
double	WeightedLPNormDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2)
double	WeightedLPNormDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2)
double	MinimumDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2)
double	MinimumDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2)
double	ArcCosineDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Computes the cosine distance for two given feature vectors.
double	ArcCosineDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Computes the cosine distance for two given feature vectors.
double	WeightedSquaredEuclideanDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the squared Euclidean distance between the given two vectors.
double	WeightedSquaredEuclideanDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the squared Euclidean distance between the given two vectors.
double	LPNormDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Returns the distance between the specified FeatureVectors as a LP-Norm for the currently set p.
double	LPNormDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Returns the distance between the specified FeatureVectors as a LP-Norm for the currently set p.
double	CosineDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Computes the cosine distance for two given feature vectors.
double	CosineDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Computes the cosine distance for two given feature vectors.
double	WeightedDistanceFunction.doubleDistance(NumberVector<?,?> o1, NumberVector<?,?> o2) Provides the Weighted distance for feature vectors.
double	WeightedDistanceFunction.doubleDistance(NumberVector<?,?> o1, NumberVector<?,?> o2) Provides the Weighted distance for feature vectors.
protected double	SquaredEuclideanDistanceFunction.doubleMinDistObject(SpatialComparable mbr, NumberVector<?,?> v)
protected double	ManhattanDistanceFunction.doubleMinDistObject(SpatialComparable mbr, NumberVector<?,?> v)
protected double	EuclideanDistanceFunction.doubleMinDistObject(SpatialComparable mbr, NumberVector<?,?> v)

Uses of NumberVector in de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram

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

<T extends NumberVector<?,?>> SpatialDistanceQuery<T,DoubleDistance>

HistogramIntersectionDistanceFunction.instantiate(Relation<T> relation)

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

double	HistogramIntersectionDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2)
double	HistogramIntersectionDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2)

Uses of NumberVector in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation

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

static class	ERiCDistanceFunction.Instance<V extends NumberVector<?,?>> The actual instance bound to a particular database.
static class	PCABasedCorrelationDistanceFunction.Instance<V extends NumberVector<?,?>> The actual instance bound to a particular database.

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

<T extends NumberVector<?,?>> PCABasedCorrelationDistanceFunction.Instance<T>	PCABasedCorrelationDistanceFunction.instantiate(Relation<T> database)
<T extends NumberVector<?,?>> ERiCDistanceFunction.Instance<T>	ERiCDistanceFunction.instantiate(Relation<T> database)

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

BitDistance	ERiCDistanceFunction.distance(NumberVector<?,?> v1, NumberVector<?,?> v2, PCAFilteredResult pca1, PCAFilteredResult pca2) Computes the distance between two given DatabaseObjects according to this distance function.
BitDistance	ERiCDistanceFunction.distance(NumberVector<?,?> v1, NumberVector<?,?> v2, PCAFilteredResult pca1, PCAFilteredResult pca2) Computes the distance between two given DatabaseObjects according to this distance function.
double	SquaredPearsonCorrelationDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Computes the squared Pearson correlation distance for two given feature vectors.
double	SquaredPearsonCorrelationDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Computes the squared Pearson correlation distance for two given feature vectors.
double	PearsonCorrelationDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Computes the Pearson correlation distance for two given feature vectors.
double	PearsonCorrelationDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Computes the Pearson correlation distance for two given feature vectors.
double	WeightedPearsonCorrelationDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Computes the Pearson correlation distance for two given feature vectors.
double	WeightedPearsonCorrelationDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Computes the Pearson correlation distance for two given feature vectors.
double	WeightedSquaredPearsonCorrelationDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Computes the squared Pearson correlation distance for two given feature vectors.
double	WeightedSquaredPearsonCorrelationDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Computes the squared Pearson correlation distance for two given feature vectors.

Constructor parameters in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation with type arguments of type NumberVector

ERiCDistanceFunction(IndexFactory<NumberVector<?,?>,FilteredLocalPCAIndex<NumberVector<?,?>>> indexFactory, double delta, double tau)
Constructor.

ERiCDistanceFunction(IndexFactory<NumberVector<?,?>,FilteredLocalPCAIndex<NumberVector<?,?>>> indexFactory, double delta, double tau)
Constructor.

PCABasedCorrelationDistanceFunction(IndexFactory<NumberVector<?,?>,FilteredLocalPCAIndex<NumberVector<?,?>>> indexFactory, double delta)
Constructor

PCABasedCorrelationDistanceFunction(IndexFactory<NumberVector<?,?>,FilteredLocalPCAIndex<NumberVector<?,?>>> indexFactory, double delta)
Constructor

Uses of NumberVector in de.lmu.ifi.dbs.elki.distance.distancefunction.geo

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.geo that return types with arguments of type NumberVector

SimpleTypeInformation<? super NumberVector<?,?>>	LngLatDistanceFunction.getInputTypeRestriction()
SimpleTypeInformation<? super NumberVector<?,?>>	LatLngDistanceFunction.getInputTypeRestriction()
SimpleTypeInformation<? super NumberVector<?,?>>	DimensionSelectingLatLngDistanceFunction.getInputTypeRestriction()

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

double	LngLatDistanceFunction.doubleDistance(NumberVector<?,?> o1, NumberVector<?,?> o2)
double	LngLatDistanceFunction.doubleDistance(NumberVector<?,?> o1, NumberVector<?,?> o2)
double	LatLngDistanceFunction.doubleDistance(NumberVector<?,?> o1, NumberVector<?,?> o2)
double	LatLngDistanceFunction.doubleDistance(NumberVector<?,?> o1, NumberVector<?,?> o2)
double	DimensionSelectingLatLngDistanceFunction.doubleDistance(NumberVector<?,?> o1, NumberVector<?,?> o2)
double	DimensionSelectingLatLngDistanceFunction.doubleDistance(NumberVector<?,?> o1, NumberVector<?,?> o2)

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

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

class	AbstractPreferenceVectorBasedCorrelationDistanceFunction<V extends NumberVector<?,?>,P extends PreferenceVectorIndex<V>> Abstract super class for all preference vector based correlation distance functions.
static class	AbstractPreferenceVectorBasedCorrelationDistanceFunction.Instance<V extends NumberVector<?,?>,P extends PreferenceVectorIndex<V>> Instance to compute the distances on an actual database.
static class	DiSHDistanceFunction.Instance<V extends NumberVector<?,?>> The actual instance bound to a particular database.
class	HiSCDistanceFunction<V extends NumberVector<?,?>> Distance function used in the HiSC algorithm.
static class	HiSCDistanceFunction.Instance<V extends NumberVector<?,?>> The actual instance bound to a particular database.
static class	HiSCDistanceFunction.Parameterizer<V extends NumberVector<?,?>> Parameterization class.
static class	SubspaceDistanceFunction.Instance<V extends NumberVector<?,?>> The actual instance bound to a particular database.

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

<T extends NumberVector<?,?>> SpatialPrimitiveDistanceQuery<T,DoubleDistance>	DimensionsSelectingEuclideanDistanceFunction.instantiate(Relation<T> database)
<T extends NumberVector<?,?>> DiSHDistanceFunction.Instance<T>	DiSHDistanceFunction.instantiate(Relation<T> database)
<T extends NumberVector<?,?>> SpatialPrimitiveDistanceQuery<T,DoubleDistance>	DimensionSelectingDistanceFunction.instantiate(Relation<T> database)
<V extends NumberVector<?,?>> SubspaceDistanceFunction.Instance<V>	SubspaceDistanceFunction.instantiate(Relation<V> database)

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace that return types with arguments of type NumberVector

VectorFieldTypeInformation<? super NumberVector<?,?>>	DimensionsSelectingEuclideanDistanceFunction.getInputTypeRestriction()
VectorTypeInformation<? super NumberVector<?,?>>	DimensionSelectingDistanceFunction.getInputTypeRestriction()

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

DoubleDistance	DimensionSelectingDistanceFunction.distance(NumberVector<?,?> o1, NumberVector<?,?> o2)
DoubleDistance	DimensionSelectingDistanceFunction.distance(NumberVector<?,?> o1, NumberVector<?,?> o2)
double	DimensionsSelectingEuclideanDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the Euclidean distance between two given feature vectors in the selected dimensions.
double	DimensionsSelectingEuclideanDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the Euclidean distance between two given feature vectors in the selected dimensions.
double	DimensionSelectingDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Computes the distance between two given DatabaseObjects according to this distance function.
double	DimensionSelectingDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Computes the distance between two given DatabaseObjects according to this distance function.
protected double	DimensionsSelectingEuclideanDistanceFunction.doubleMinDistObject(SpatialComparable mbr, NumberVector<?,?> v)

Constructor parameters in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace with type arguments of type NumberVector

DiSHDistanceFunction(DiSHPreferenceVectorIndex.Factory<NumberVector<?,?>> indexFactory, double epsilon)
Constructor.

SubspaceDistanceFunction(IndexFactory<NumberVector<?,?>,FilteredLocalPCAIndex<NumberVector<?,?>>> indexFactory)
Constructor

SubspaceDistanceFunction(IndexFactory<NumberVector<?,?>,FilteredLocalPCAIndex<NumberVector<?,?>>> indexFactory)
Constructor

Uses of NumberVector in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries that return types with arguments of type NumberVector

VectorFieldTypeInformation<? super NumberVector<?,?>>	AbstractEditDistanceFunction.getInputTypeRestriction()
VectorFieldTypeInformation<? super NumberVector<?,?>>	LCSSDistanceFunction.getInputTypeRestriction()

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

double	ERPDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the Edit Distance With Real Penalty distance between the given two vectors.
double	ERPDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the Edit Distance With Real Penalty distance between the given two vectors.
double	EDRDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the Edit Distance on Real Sequence distance between the given two vectors.
double	EDRDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the Edit Distance on Real Sequence distance between the given two vectors.
double	DTWDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the Dynamic Time Warping distance between the given two vectors.
double	DTWDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the Dynamic Time Warping distance between the given two vectors.
double	LCSSDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the Longest Common Subsequence distance between the given two vectors.
double	LCSSDistanceFunction.doubleDistance(NumberVector<?,?> v1, NumberVector<?,?> v2) Provides the Longest Common Subsequence distance between the given two vectors.

Uses of NumberVector in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel

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

class

LinearKernelFunction<O extends NumberVector<?,?>> Provides a linear Kernel function that computes a similarity between the two feature vectors V1 and V2 defined by V1^T*V2.

Methods in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel with type parameters of type NumberVector

<T extends NumberVector<?,?>> DistanceSimilarityQuery<T,DoubleDistance>	FooKernelFunction.instantiate(Relation<T> database)
<T extends NumberVector<?,?>> DistanceSimilarityQuery<T,DoubleDistance>	PolynomialKernelFunction.instantiate(Relation<T> database)

Methods in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel that return types with arguments of type NumberVector

VectorFieldTypeInformation<? super NumberVector<?,?>>	FooKernelFunction.getInputTypeRestriction()
VectorFieldTypeInformation<? super NumberVector<?,?>>	PolynomialKernelFunction.getInputTypeRestriction()

Methods in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel with parameters of type NumberVector

DoubleDistance	FooKernelFunction.distance(NumberVector<?,?> fv1, NumberVector<?,?> fv2)
DoubleDistance	FooKernelFunction.distance(NumberVector<?,?> fv1, NumberVector<?,?> fv2)
DoubleDistance	PolynomialKernelFunction.distance(NumberVector<?,?> fv1, NumberVector<?,?> fv2)
DoubleDistance	PolynomialKernelFunction.distance(NumberVector<?,?> fv1, NumberVector<?,?> fv2)
DoubleDistance	FooKernelFunction.similarity(NumberVector<?,?> o1, NumberVector<?,?> o2) Provides an experimental kernel similarity between the given two vectors.
DoubleDistance	FooKernelFunction.similarity(NumberVector<?,?> o1, NumberVector<?,?> o2) Provides an experimental kernel similarity between the given two vectors.
DoubleDistance	PolynomialKernelFunction.similarity(NumberVector<?,?> o1, NumberVector<?,?> o2) Provides the linear kernel similarity between the given two vectors.
DoubleDistance	PolynomialKernelFunction.similarity(NumberVector<?,?> o1, NumberVector<?,?> o2) Provides the linear kernel similarity between the given two vectors.

Uses of NumberVector in de.lmu.ifi.dbs.elki.index.preprocessed

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

interface	LocalProjectionIndex<V extends NumberVector<?,?>,P extends ProjectionResult> Abstract index interface for local projections
static interface	LocalProjectionIndex.Factory<V extends NumberVector<?,?>,I extends LocalProjectionIndex<V,?>> Factory

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

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

class	MetricalIndexApproximationMaterializeKNNPreprocessor<O extends NumberVector<? super O,?>,D extends Distance<D>,N extends Node<E>,E extends MTreeEntry<D>> A preprocessor for annotation of the k nearest neighbors (and their distances) to each database object.
static class	MetricalIndexApproximationMaterializeKNNPreprocessor.Factory<O extends NumberVector<? super O,?>,D extends Distance<D>,N extends Node<E>,E extends MTreeEntry<D>> The parameterizable factory.
static class	MetricalIndexApproximationMaterializeKNNPreprocessor.Factory.Parameterizer<O extends NumberVector<? super O,?>,D extends Distance<D>,N extends Node<E>,E extends MTreeEntry<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.

Methods in de.lmu.ifi.dbs.elki.index.preprocessed.knn that return types with arguments of type NumberVector

SpatialApproximationMaterializeKNNPreprocessor<NumberVector<?,?>,D,N,E>

SpatialApproximationMaterializeKNNPreprocessor.Factory.instantiate(Relation<NumberVector<?,?>> relation)

Method parameters in de.lmu.ifi.dbs.elki.index.preprocessed.knn with type arguments of type NumberVector

SpatialApproximationMaterializeKNNPreprocessor<NumberVector<?,?>,D,N,E>

SpatialApproximationMaterializeKNNPreprocessor.Factory.instantiate(Relation<NumberVector<?,?>> relation)

Constructor parameters in de.lmu.ifi.dbs.elki.index.preprocessed.knn with type arguments of type NumberVector

SpatialApproximationMaterializeKNNPreprocessor.Factory(int k, DistanceFunction<? super NumberVector<?,?>,D> distanceFunction)
Constructor.

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

Classes in de.lmu.ifi.dbs.elki.index.preprocessed.localpca with type parameters of type NumberVector

class	AbstractFilteredPCAIndex<NV extends NumberVector<? extends NV,?>> Abstract base class for a local PCA based index.
static class	AbstractFilteredPCAIndex.Factory<NV extends NumberVector<NV,?>,I extends AbstractFilteredPCAIndex<NV>> Factory class
static class	AbstractFilteredPCAIndex.Factory.Parameterizer<NV extends NumberVector<NV,?>,I extends AbstractFilteredPCAIndex<NV>> Parameterization class.
interface	FilteredLocalPCAIndex<NV extends NumberVector<?,?>> Interface for an index providing local PCA results.
static interface	FilteredLocalPCAIndex.Factory<NV extends NumberVector<?,?>,I extends FilteredLocalPCAIndex<NV>> Factory interface
class	KNNQueryFilteredPCAIndex<NV extends NumberVector<? extends NV,?>> Provides the local neighborhood to be considered in the PCA as the k nearest neighbors of an object.
static class	KNNQueryFilteredPCAIndex.Factory<V extends NumberVector<V,?>> Factory class
static class	KNNQueryFilteredPCAIndex.Factory.Parameterizer<NV extends NumberVector<NV,?>> Parameterization class.
class	RangeQueryFilteredPCAIndex<NV extends NumberVector<? extends NV,?>> Provides the local neighborhood to be considered in the PCA as the neighbors within an epsilon range query of an object.
static class	RangeQueryFilteredPCAIndex.Factory<V extends NumberVector<V,?>> Factory class
static class	RangeQueryFilteredPCAIndex.Factory.Parameterizer<NV extends NumberVector<NV,?>> Parameterization class.

Uses of NumberVector in de.lmu.ifi.dbs.elki.index.preprocessed.preference

Classes in de.lmu.ifi.dbs.elki.index.preprocessed.preference with type parameters of type NumberVector

class	AbstractPreferenceVectorIndex<NV extends NumberVector<?,?>> Abstract base class for preference vector based algorithms.
static class	AbstractPreferenceVectorIndex.Factory<V extends NumberVector<?,?>,I extends PreferenceVectorIndex<V>> Factory class
class	DiSHPreferenceVectorIndex<V extends NumberVector<?,?>> Preprocessor for DiSH preference vector assignment to objects of a certain database.
static class	DiSHPreferenceVectorIndex.Factory<V extends NumberVector<?,?>> Factory class
static class	DiSHPreferenceVectorIndex.Factory.Parameterizer<V extends NumberVector<?,?>> Parameterization class.
class	HiSCPreferenceVectorIndex<V extends NumberVector<?,?>> Preprocessor for HiSC preference vector assignment to objects of a certain database.
static class	HiSCPreferenceVectorIndex.Factory<V extends NumberVector<?,?>> Factory class
static class	HiSCPreferenceVectorIndex.Factory.Parameterizer<V extends NumberVector<?,?>> Parameterization class.
interface	PreferenceVectorIndex<NV extends NumberVector<?,?>> Interface for an index providing preference vectors.
static interface	PreferenceVectorIndex.Factory<V extends NumberVector<?,?>,I extends PreferenceVectorIndex<V>> Factory interface

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

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

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<V,?>,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<V,?>,D extends Distance<D>> Factory class for 4C preprocessors.
static class	FourCSubspaceIndex.Factory.Parameterizer<V extends NumberVector<V,?>,D extends Distance<D>> Parameterization class.
class	PreDeConSubspaceIndex<V extends NumberVector<? extends V,?>,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<? extends V,?>,D extends Distance<D>> Factory
static class	PreDeConSubspaceIndex.Factory.Parameterizer<V extends NumberVector<? extends V,?>,D extends Distance<D>> Parameterization class.
interface	SubspaceProjectionIndex<NV extends NumberVector<?,?>,P extends ProjectionResult> Interface for an index providing local subspaces.
static interface	SubspaceProjectionIndex.Factory<NV extends NumberVector<?,?>,I extends SubspaceProjectionIndex<NV,?>> Factory interface

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

Constructors in de.lmu.ifi.dbs.elki.index.tree.spatial with parameters of type NumberVector

SpatialPointLeafEntry(DBID id, NumberVector<?,?> vector)
Constructor from number vector

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

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

class	AbstractRStarTreeFactory<O extends NumberVector<O,?>,N extends AbstractRStarTreeNode<N,E>,E extends SpatialEntry,I extends AbstractRStarTree<N,E> & Index> Abstract factory for R*-Tree based trees.
static class	AbstractRStarTreeFactory.Parameterizer<O extends NumberVector<O,?>> Parameterization class.

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

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

class	DeLiCluTreeFactory<O extends NumberVector<O,?>> Factory for DeLiClu R*-Trees.
static class	DeLiCluTreeFactory.Parameterizer<O extends NumberVector<O,?>> Parameterization class.
class	DeLiCluTreeIndex<O extends NumberVector<?,?>> The common use of the DeLiClu tree: indexing number vectors.

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

DeLiCluLeafEntry(DBID id, NumberVector<?,?> vector)
Constructs a new LeafEntry object with the given parameters.

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

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

class	RStarTreeFactory<O extends NumberVector<O,?>> Factory for regular R*-Trees.
static class	RStarTreeFactory.Parameterizer<O extends NumberVector<O,?>> Parameterization class.
class	RStarTreeIndex<O extends NumberVector<?,?>> The common use of the rstar tree: indexing number vectors.

Uses of NumberVector in de.lmu.ifi.dbs.elki.math

Methods in de.lmu.ifi.dbs.elki.math with parameters of type NumberVector

static double	MathUtil.pearsonCorrelationCoefficient(NumberVector<?,?> x, NumberVector<?,?> y) Provides the Pearson product-moment correlation coefficient for two FeatureVectors.
static double	MathUtil.pearsonCorrelationCoefficient(NumberVector<?,?> x, NumberVector<?,?> y) Provides the Pearson product-moment correlation coefficient for two FeatureVectors.
static double	MathUtil.weightedPearsonCorrelationCoefficient(NumberVector<?,?> x, NumberVector<?,?> y, double[] weights) Provides the Pearson product-moment correlation coefficient for two FeatureVectors.
static double	MathUtil.weightedPearsonCorrelationCoefficient(NumberVector<?,?> x, NumberVector<?,?> y, double[] weights) Provides the Pearson product-moment correlation coefficient for two FeatureVectors.

Uses of NumberVector in de.lmu.ifi.dbs.elki.math.linearalgebra

Methods in de.lmu.ifi.dbs.elki.math.linearalgebra with type parameters of type NumberVector

<F extends NumberVector<? extends F,?>> F	CovarianceMatrix.getMeanVector(Relation<? extends F> relation) Get the mean as vector.
<F extends NumberVector<? extends F,?>> F	Centroid.toVector(Relation<? extends F> relation) Get the data as vector

Methods in de.lmu.ifi.dbs.elki.math.linearalgebra with parameters of type NumberVector

void	ProjectedCentroid.put(NumberVector<?,?> val) Add a single value with weight 1.0
void	Centroid.put(NumberVector<?,?> val) Add a single value with weight 1.0
void	CovarianceMatrix.put(NumberVector<?,?> val) Add a single value with weight 1.0
void	ProjectedCentroid.put(NumberVector<?,?> val, double weight) Add data with a given weight.
void	Centroid.put(NumberVector<?,?> val, double weight) Add data with a given weight.
void	CovarianceMatrix.put(NumberVector<?,?> val, double weight) Add data with a given weight.

Method parameters in de.lmu.ifi.dbs.elki.math.linearalgebra with type arguments of type NumberVector

static ProjectedCentroid	ProjectedCentroid.make(BitSet dims, Relation<? extends NumberVector<?,?>> relation) Static Constructor from a relation.
static ProjectedCentroid	ProjectedCentroid.make(BitSet dims, Relation<? extends NumberVector<?,?>> relation, Iterable<DBID> ids) Static Constructor from a relation.
static Centroid	Centroid.make(Relation<? extends NumberVector<?,?>> relation) Static constructor from an existing relation.
static CovarianceMatrix	CovarianceMatrix.make(Relation<? extends NumberVector<?,?>> relation) Static Constructor from a full relation.
static Centroid	Centroid.make(Relation<? extends NumberVector<?,?>> relation, Iterable<DBID> ids) Static constructor from an existing relation.
static CovarianceMatrix	CovarianceMatrix.make(Relation<? extends NumberVector<?,?>> relation, Iterable<DBID> ids) Static Constructor from a full relation.

Uses of NumberVector in de.lmu.ifi.dbs.elki.math.linearalgebra.pca

Classes in de.lmu.ifi.dbs.elki.math.linearalgebra.pca with type parameters of type NumberVector

class	AbstractCovarianceMatrixBuilder<V extends NumberVector<? extends V,?>> Abstract class with the task of computing a Covariance matrix to be used in PCA.
interface	CovarianceMatrixBuilder<V extends NumberVector<? extends V,?>> Interface for computing covariance matrixes on a data set.
class	PCAFilteredRunner<V extends NumberVector<? extends V,?>> PCA runner that will do dimensionality reduction.
static class	PCAFilteredRunner.Parameterizer<V extends NumberVector<? extends V,?>> Parameterization class.
class	PCARunner<V extends NumberVector<? extends V,?>> Class to run PCA on given data.
static class	PCARunner.Parameterizer<V extends NumberVector<? extends V,?>> Parameterization class.
class	StandardCovarianceMatrixBuilder<V extends NumberVector<? extends V,?>> Class for building a "traditional" covariance matrix.
class	WeightedCovarianceMatrixBuilder<V extends NumberVector<? extends V,?>> CovarianceMatrixBuilder with weights.
static class	WeightedCovarianceMatrixBuilder.Parameterizer<V extends NumberVector<V,?>> Parameterization class.

Uses of NumberVector in de.lmu.ifi.dbs.elki.math.spacefillingcurves

Methods in de.lmu.ifi.dbs.elki.math.spacefillingcurves with parameters of type NumberVector

BigInteger	ZCurve.Transformer.asBigInteger(NumberVector<?,?> vector) Transform a single vector.
byte[]	ZCurve.Transformer.asByteArray(NumberVector<?,?> vector) Transform a single vector.

Constructor parameters in de.lmu.ifi.dbs.elki.math.spacefillingcurves with type arguments of type NumberVector

ZCurve.Transformer(Relation<? extends NumberVector<?,?>> relation, DBIDs ids)
Constructor.

Uses of NumberVector in de.lmu.ifi.dbs.elki.utilities

Methods in de.lmu.ifi.dbs.elki.utilities with type parameters of type NumberVector

static <V extends NumberVector<? extends V,?>> V	DatabaseUtil.centroid(Relation<? extends V> relation) Returns the centroid as a NumberVector object of the specified database.
static <V extends NumberVector<? extends V,?>> V	DatabaseUtil.centroid(Relation<? extends V> relation, DBIDs ids) Returns the centroid as a NumberVector object of the specified objects stored in the given database.
static <V extends NumberVector<? extends V,?>> V	DatabaseUtil.centroid(Relation<? extends V> relation, DBIDs ids, BitSet dimensions) Returns the centroid w.r.t. the dimensions specified by the given BitSet as a NumberVector object of the specified objects stored in the given database.
static <NV extends NumberVector<NV,?>> Pair<NV,NV>	DatabaseUtil.computeMinMax(Relation<NV> database) Determines the minimum and maximum values in each dimension of all objects stored in the given database.
static <V extends NumberVector<? extends V,?>> Matrix	DatabaseUtil.covarianceMatrix(Relation<? extends V> database, DBIDs ids) Determines the covariance matrix of the objects stored in the given database.
static <V extends NumberVector<?,?>> double	DatabaseUtil.exactMedian(Relation<V> relation, DBIDs ids, int dimension) Returns the median of a data set in the given dimension.
static <V extends NumberVector<?,?>> double	DatabaseUtil.quickMedian(Relation<V> relation, ArrayDBIDs ids, int dimension, int numberOfSamples) Returns the median of a data set in the given dimension by using a sampling method.
static <V extends NumberVector<?,?>,T extends NumberVector<?,?>> Relation<V>	DatabaseUtil.relationUglyVectorCast(Relation<T> database) An ugly vector type cast unavoidable in some situations due to Generics.
static <V extends NumberVector<?,?>,T extends NumberVector<?,?>> Relation<V>	DatabaseUtil.relationUglyVectorCast(Relation<T> database) An ugly vector type cast unavoidable in some situations due to Generics.
static <V extends NumberVector<? extends V,?>> double[]	DatabaseUtil.variances(Relation<V> database) Determines the variances in each dimension of all objects stored in the given database.
static <V extends NumberVector<? extends V,?>> double[]	DatabaseUtil.variances(Relation<V> database, DBIDs ids) Determines the variances in each dimension of the specified objects stored in the given database.

Methods in de.lmu.ifi.dbs.elki.utilities with parameters of type NumberVector

static double[]

DatabaseUtil.variances(Relation<? extends NumberVector<?,?>> database, NumberVector<?,?> centroid, DBIDs ids) Determines the variances in each dimension of the specified objects stored in the given database.

Method parameters in de.lmu.ifi.dbs.elki.utilities with type arguments of type NumberVector

static double[]

DatabaseUtil.variances(Relation<? extends NumberVector<?,?>> database, NumberVector<?,?> centroid, DBIDs ids) Determines the variances in each dimension of the specified objects stored in the given database.

Uses of NumberVector in de.lmu.ifi.dbs.elki.utilities.referencepoints

Classes in de.lmu.ifi.dbs.elki.utilities.referencepoints with type parameters of type NumberVector

class	AxisBasedReferencePoints<V extends NumberVector<V,?>> Strategy to pick reference points by placing them on the axis ends.
static class	AxisBasedReferencePoints.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	FullDatabaseReferencePoints<O extends NumberVector<? extends O,?>> Strategy to use the complete database as reference points.
class	GridBasedReferencePoints<V extends NumberVector<V,?>> Grid-based strategy to pick reference points.
static class	GridBasedReferencePoints.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	RandomGeneratedReferencePoints<V extends NumberVector<V,?>> Reference points generated randomly within the used data space.
static class	RandomGeneratedReferencePoints.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
class	RandomSampleReferencePoints<V extends NumberVector<? extends V,?>> Random-Sampling strategy for picking reference points.
static class	RandomSampleReferencePoints.Parameterizer<V extends NumberVector<? extends V,?>> Parameterization class.
class	StarBasedReferencePoints<V extends NumberVector<V,?>> Star-based strategy to pick reference points.
static class	StarBasedReferencePoints.Parameterizer<V extends NumberVector<V,?>> Parameterization class.

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

Methods in de.lmu.ifi.dbs.elki.visualization.projections with type parameters of type NumberVector

<NV extends NumberVector<NV,?>> NV	AbstractProjection.projectRelativeRenderToDataSpace(Vector v, NV prototype) Project a relative vector from rendering space to data space.
<NV extends NumberVector<NV,?>> NV	Projection.projectRelativeRenderToDataSpace(Vector v, NV prototype) Project a relative vector from rendering space to data space.
<NV extends NumberVector<NV,?>> NV	AbstractProjection.projectRelativeScaledToDataSpace(Vector v, NV prototype) Project a relative vector from scaled space to data space.
<NV extends NumberVector<NV,?>> NV	Projection.projectRelativeScaledToDataSpace(Vector v, NV prototype) Project a relative vector from scaled space to data space.
<NV extends NumberVector<NV,?>> NV	AbstractProjection.projectRenderToDataSpace(Vector v, NV prototype) Project a vector from rendering space to data space.
<NV extends NumberVector<NV,?>> NV	Projection.projectRenderToDataSpace(Vector v, NV prototype) Project a vector from rendering space to data space.
<NV extends NumberVector<NV,?>> NV	AbstractProjection.projectScaledToDataSpace(Vector v, NV factory) Project a vector from scaled space to data space.
<NV extends NumberVector<NV,?>> NV	Projection.projectScaledToDataSpace(Vector v, NV factory) Project a vector from scaled space to data space.

Methods in de.lmu.ifi.dbs.elki.visualization.projections with parameters of type NumberVector

double[]	AffineProjection.fastProjectDataToRenderSpace(NumberVector<?,?> data)
double	Simple1D.fastProjectDataToRenderSpace(NumberVector<?,?> data)
double	Projection1D.fastProjectDataToRenderSpace(NumberVector<?,?> data) Project a data vector from data space to rendering space.
double[]	Simple2D.fastProjectDataToRenderSpace(NumberVector<?,?> data)
double[]	Projection2D.fastProjectDataToRenderSpace(NumberVector<?,?> data) Project a data vector from data space to rendering space.
double[]	AffineProjection.fastProjectRelativeDataToRenderSpace(NumberVector<?,?> data)
double	Simple1D.fastProjectRelativeDataToRenderSpace(NumberVector<?,?> data)
double	Projection1D.fastProjectRelativeDataToRenderSpace(NumberVector<?,?> data) Project a data vector from data space to rendering space.
double[]	Simple2D.fastProjectRelativeDataToRenderSpace(NumberVector<?,?> data)
double[]	Projection2D.fastProjectRelativeDataToRenderSpace(NumberVector<?,?> data) Project a data vector from data space to rendering space.
Vector	AbstractProjection.projectDataToRenderSpace(NumberVector<?,?> data) Project a data vector from data space to rendering space.
Vector	Projection.projectDataToRenderSpace(NumberVector<?,?> data) Project a data vector from data space to rendering space.
Vector	AbstractProjection.projectDataToScaledSpace(NumberVector<?,?> data) Project a data vector from data space to scaled space.
Vector	Projection.projectDataToScaledSpace(NumberVector<?,?> data) Project a data vector from data space to scaled space.
Vector	AbstractProjection.projectRelativeDataToRenderSpace(NumberVector<?,?> data) Project a relative data vector from data space to rendering space.
Vector	Projection.projectRelativeDataToRenderSpace(NumberVector<?,?> data) Project a relative data vector from data space to rendering space.
Vector	AbstractProjection.projectRelativeDataToScaledSpace(NumberVector<?,?> data) Project a relative data vector from data space to scaled space.
Vector	Projection.projectRelativeDataToScaledSpace(NumberVector<?,?> data) Project a relative data vector from data space to scaled space.

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

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

class	HistogramProjector<V extends NumberVector<?,?>> ScatterPlotProjector is responsible for producing a set of scatterplot visualizations.
class	ScatterPlotProjector<V extends NumberVector<?,?>> ScatterPlotProjector is responsible for producing a set of scatterplot visualizations.

Uses of NumberVector in de.lmu.ifi.dbs.elki.visualization.scales

Methods in de.lmu.ifi.dbs.elki.visualization.scales with type parameters of type NumberVector

static <O extends NumberVector<?,? extends Number>> LinearScale[]

Scales.calcScales(Relation<O> db) Compute a linear scale for each dimension.

Uses of NumberVector in de.lmu.ifi.dbs.elki.visualization.svg

Methods in de.lmu.ifi.dbs.elki.visualization.svg with type parameters of type NumberVector

static <V extends NumberVector<V,?>,D extends NumberDistance<?,?>> Element	SVGHyperSphere.drawCross(SVGPlot svgp, Projection2D proj, V mid, D rad) Wireframe "cross" hypersphere
static <V extends NumberVector<V,?>,D extends NumberDistance<?,?>> Element	SVGHyperSphere.drawEuclidean(SVGPlot svgp, Projection2D proj, V mid, D rad) Wireframe "euclidean" hypersphere
static <V extends NumberVector<V,?>> Element	SVGHyperCube.drawFilled(SVGPlot svgp, String cls, Projection2D proj, V min, V max) Filled hypercube.
static <V extends NumberVector<V,?>> Element	SVGHyperCube.drawFrame(SVGPlot svgp, Projection2D proj, V min, V max) Wireframe hypercube.
static <V extends NumberVector<V,?>,D extends NumberDistance<?,?>> Element	SVGHyperSphere.drawLp(SVGPlot svgp, Projection2D proj, V mid, D rad, double p) Wireframe "Lp" hypersphere
static <V extends NumberVector<V,?>,D extends NumberDistance<?,?>> Element	SVGHyperSphere.drawManhattan(SVGPlot svgp, Projection2D proj, V mid, D rad) Wireframe "manhattan" hypersphere

Uses of NumberVector in de.lmu.ifi.dbs.elki.visualization.visualizers

Methods in de.lmu.ifi.dbs.elki.visualization.visualizers that return types with arguments of type NumberVector

static Iterator<Relation<? extends NumberVector<?,?>>>

VisualizerUtil.iterateVectorFieldRepresentations(Result result) Filter for number vector field representations

Uses of NumberVector in de.lmu.ifi.dbs.elki.visualization.visualizers.vis1d

Classes in de.lmu.ifi.dbs.elki.visualization.visualizers.vis1d with type parameters of type NumberVector

class	P1DHistogramVisualizer<NV extends NumberVector<NV,?>> Generates a SVG-Element containing a histogram representing the distribution of the database's objects.
static class	P1DHistogramVisualizer.Factory<NV extends NumberVector<NV,?>> Visualizer factory for 1D histograms
static class	P1DHistogramVisualizer.Factory.Parameterizer<NV extends NumberVector<NV,?>> Parameterization class.

Uses of NumberVector in de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d

Classes in de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d with type parameters of type NumberVector

class	AbstractTooltipVisualization<NV extends NumberVector<NV,?>> General base class for a tooltip visualizer.
class	AxisVisualization<NV extends NumberVector<NV,?>> Generates a SVG-Element containing axes, including labeling.
static class	AxisVisualization.Factory<NV extends NumberVector<NV,?>> Factory for axis visualizations
class	BubbleVisualization<NV extends NumberVector<NV,?>> Generates a SVG-Element containing bubbles.
static class	BubbleVisualization.Factory<NV extends NumberVector<NV,?>> Factory for producing bubble visualizations
static class	BubbleVisualization.Factory.Parameterizer<NV extends NumberVector<NV,?>> Parameterization class.
class	ClusterConvexHullVisualization<NV extends NumberVector<NV,?>> Visualizer for generating an SVG-Element containing the convex hull of each cluster.
static class	ClusterConvexHullVisualization.Factory<NV extends NumberVector<NV,?>> Factory for visualizers to generate an SVG-Element containing the convex hull of a cluster.
class	ClusteringVisualization<NV extends NumberVector<NV,?>> Visualize a clustering using different markers for different clusters.
static class	ClusteringVisualization.Factory<NV extends NumberVector<NV,?>> Visualization factory
class	ClusterMeanVisualization<NV extends NumberVector<NV,?>> Visualize the mean of a KMeans-Clustering
static class	ClusterMeanVisualization.Factory<NV extends NumberVector<NV,?>> Factory for visualizers to generate an SVG-Element containing a marker for the mean in a KMeans-Clustering
class	ClusterOrderVisualization<NV extends NumberVector<NV,?>> Cluster order visualizer.
static class	ClusterOrderVisualization.Factory<NV extends NumberVector<NV,?>> Visualize an OPTICS cluster order by drawing connection lines.
class	DotVisualization<NV extends NumberVector<NV,?>> Generates a SVG-Element containing "dots" as markers representing the Database's objects.
static class	DotVisualization.Factory<NV extends NumberVector<NV,?>> The visualization factory
class	EMClusterVisualization<NV extends NumberVector<NV,?>> Visualizer for generating SVG-Elements containing ellipses for first, second and third standard deviation
static class	EMClusterVisualization.Factory<NV extends NumberVector<NV,?>> Visualizer for generating SVG-Elements containing ellipses for first, second and third standard deviation
class	MoveObjectsToolVisualization<NV extends NumberVector<NV,?>> Tool to move the currently selected objects.
static class	MoveObjectsToolVisualization.Factory<NV extends NumberVector<NV,?>> Factory for tool visualizations for changing objects in the database
class	P2DVisualization<NV extends NumberVector<?,?>> Default class to handle 2D projected visualizations.
class	PolygonVisualization<V extends NumberVector<?,?>> Renders PolygonsObject in the data set.
class	ReferencePointsVisualization<NV extends NumberVector<NV,?>> The actual visualization instance, for a single projection
static class	ReferencePointsVisualization.Factory<NV extends NumberVector<NV,?>> Generates a SVG-Element visualizing reference points.
class	SelectionConvexHullVisualization<NV extends NumberVector<NV,?>> Visualizer for generating an SVG-Element containing the convex hull of the selected points
static class	SelectionConvexHullVisualization.Factory<NV extends NumberVector<NV,?>> Factory for visualizers to generate an SVG-Element containing the convex hull of the selected points
class	SelectionCubeVisualization<NV extends NumberVector<NV,?>> Visualizer for generating an SVG-Element containing a cube as marker representing the selected range for each dimension
static class	SelectionCubeVisualization.Factory<NV extends NumberVector<NV,?>> Factory for visualizers to generate an SVG-Element containing a cube as marker representing the selected range for each dimension
static class	SelectionCubeVisualization.Factory.Parameterizer<NV extends NumberVector<NV,?>> Parameterization class.
class	SelectionDotVisualization<NV extends NumberVector<NV,?>> Visualizer for generating an SVG-Element containing dots as markers representing the selected Database's objects.
static class	SelectionDotVisualization.Factory<NV extends NumberVector<NV,?>> Factory for visualizers to generate an SVG-Element containing dots as markers representing the selected Database's objects.
class	SelectionToolCubeVisualization<NV extends NumberVector<NV,?>> Tool-Visualization for the tool to select ranges
static class	SelectionToolCubeVisualization.Factory<NV extends NumberVector<NV,?>> Factory for tool visualizations for selecting ranges and the inclosed objects
class	SelectionToolDotVisualization<NV extends NumberVector<NV,?>> Tool-Visualization for the tool to select objects
static class	SelectionToolDotVisualization.Factory<NV extends NumberVector<NV,?>> Factory for tool visualizations for selecting objects
class	ToolBox2DVisualization<NV extends NumberVector<NV,?>> Renders a tool box on the left of the 2D visualization
static class	ToolBox2DVisualization.Factory<NV extends NumberVector<NV,?>> Factory for visualizers for a toolbox
class	TooltipScoreVisualization<NV extends NumberVector<NV,?>> Generates a SVG-Element containing Tooltips.
static class	TooltipScoreVisualization.Factory<NV extends NumberVector<NV,?>> Factory for tooltip visualizers
static class	TooltipScoreVisualization.Factory.Parameterizer<NV extends NumberVector<NV,?>> Parameterization class.
class	TooltipStringVisualization<NV extends NumberVector<NV,?>> Generates a SVG-Element containing Tooltips.
static class	TooltipStringVisualization.Factory<NV extends NumberVector<NV,?>> Factory
class	TreeMBRVisualization<NV extends NumberVector<NV,?>,N extends AbstractRStarTreeNode<N,E>,E extends SpatialEntry> Visualize the bounding rectangles of an R-Tree based index.
static class	TreeMBRVisualization.Factory<NV extends NumberVector<NV,?>> Factory
static class	TreeMBRVisualization.Factory.Parameterizer<NV extends NumberVector<NV,?>> Parameterization class.
class	TreeSphereVisualization<NV extends NumberVector<NV,?>,D extends NumberDistance<D,?>,N extends AbstractMTreeNode<NV,D,N,E>,E extends MTreeEntry<D>> Visualize the bounding sphere of a metric index.
static class	TreeSphereVisualization.Factory<NV extends NumberVector<NV,?>> Factory
static class	TreeSphereVisualization.Factory.Parameterizer<NV extends NumberVector<NV,?>> Parameterization class.

Methods in de.lmu.ifi.dbs.elki.visualization.visualizers.vis2d with type parameters of type NumberVector

private static <NV extends NumberVector<NV,?>> Clustering<MeanModel<NV>>	ClusterMeanVisualization.Factory.findMeanModel(Clustering<?> c) Test if the given clustering has a mean model.
private static <NV extends NumberVector<NV,?>> Clustering<MeanModel<NV>>	EMClusterVisualization.Factory.findMeanModel(Clustering<?> c) Test if the given clustering has a mean model.