Uses of Class
de.lmu.ifi.dbs.elki.data.RealVector

Packages that use RealVector

de.lmu.ifi.dbs.elki.algorithm	Package to collect algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.clustering	Package collects clustering algorithms.
de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering	Package to collect biclustering algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation	Package to collect correlation clustering algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace	Package to collect algorithms for clustering in axis-parallel subspaces, suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique	Helper classes for the CLIQUE algorithm.
de.lmu.ifi.dbs.elki.algorithm.result	Package to collect result classes for the results of algorithms.
de.lmu.ifi.dbs.elki.algorithm.result.clustering	Package to collect result classes for the results of clustering algorithms.
de.lmu.ifi.dbs.elki.algorithm.result.clustering.biclustering	Package to collect result classes for the results of biclustering algorithms.
de.lmu.ifi.dbs.elki.data	Package collects basic classes for different data types, database object types and label types.
de.lmu.ifi.dbs.elki.distance.distancefunction	Package collects distance functions.
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel	Package collects kernel functions.
de.lmu.ifi.dbs.elki.normalization	Provides classes and methods for normalizations (and reconstitution) of data sets.
de.lmu.ifi.dbs.elki.parser	Package collects parser for different file formats and data types.
de.lmu.ifi.dbs.elki.preprocessing	Package collects preprocessors used for data preparation in a first step of various algorithms or distance measures.
de.lmu.ifi.dbs.elki.utilities	Package collects various classes and methods of global utility.
de.lmu.ifi.dbs.elki.varianceanalysis	Classes for analysis of variance by different methods.

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

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

class

DependencyDerivator<V extends RealVector<V,?>,D extends Distance<D>> Dependency derivator computes quantitativly linear dependencies among attributes of a given dataset based on a linear correlation PCA.

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

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

class	EM<V extends RealVector<V,?>> Provides the EM algorithm (clustering by expectation maximization).
class	KMeans<D extends Distance<D>,V extends RealVector<V,?>> Provides the k-means algorithm.
class	ProjectedDBSCAN<V extends RealVector<V,?>> Provides an abstract algorithm requiring a VarianceAnalysisPreprocessor.

Uses of RealVector in de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering

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

class

AbstractBiclustering<V extends RealVector<V,Double>> Abstract class as a convenience for different biclustering approaches.

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

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

class	COPAA<V extends RealVector<V,?>> Algorithm to partition a database according to the correlation dimension of its objects and to then perform an arbitrary algorithm over the partitions.
class	COPAC<V extends RealVector<V,?>> Algorithm to partition a database according to the correlation dimension of its objects and to then perform an arbitrary clustering algorithm over the partitions.
class	ERiC<V extends RealVector<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.
class	FourC<O extends RealVector<O,?>> 4C identifies local subgroups of data objects sharing a uniform correlation.
class	ORCLUS<V extends RealVector<V,?>> ORCLUS provides the ORCLUS algorithm.

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

(package private) V

ORCLUS.Cluster.centroid The centroid of this cluster.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation that return types with arguments of type RealVector

private Database<RealVector>

CASH.buildDerivatorDB(Database<ParameterizationFunction> database, CASHInterval interval) Builds a database for the derivator consisting of the ids in the specified interval.

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

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

class	CLIQUE<V extends RealVector<V,?>> Implementation of the CLIQUE algorithm, a grid-based algorithm to identify dense clusters in subspaces of maximum dimensionality.
class	DiSH<V extends RealVector<V,?>> Algorithm for detecting subspace hierarchies.
class	PreDeCon<V extends RealVector<V,?>> PreDeCon computes clusters of subspace preference weighted connected points.
class	PROCLUS<V extends RealVector<V,?>> PROCLUS provides the PROCLUS algorithm.
class	ProjectedClustering<V extends RealVector<V,?>> Abstract superclass for PROCLUS and ORCLUS.

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

(package private) V

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

Uses of RealVector 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 RealVector

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

Uses of RealVector in de.lmu.ifi.dbs.elki.algorithm.result

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

class

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

Uses of RealVector in de.lmu.ifi.dbs.elki.algorithm.result.clustering

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

class	CLIQUEModel<V extends RealVector<V,?>> Represents a cluster model for a cluster in the CLIQUE algorithm.
class	ClustersPlusNoisePlusCorrelationAnalysis<V extends RealVector<V,?>> Provides a result of a clustering-algorithm that computes several clusters and remaining noise and a correlation analysis for each cluster.
class	EMClusters<V extends RealVector<V,?>> // todo arthur comment
class	EMModel<V extends RealVector<V,?>> // todo arthur comment
class	HierarchicalAxesParallelCorrelationClusters<V extends RealVector<V,?>,D extends Distance<D>> Provides a result of a clustering algorithm that computes hierarchical axes parallel correlation clusters from a cluster order.
class	HierarchicalCorrelationCluster<V extends RealVector<V,?>> Provides a hierarchical correlation cluster in an arbitrary subspace that holds the PCA, the ids of the objects belonging to this cluster and the children and parents of this cluster.
class	HierarchicalCorrelationClusters<V extends RealVector<V,?>> Provides a result of a clustering algorithm that computes hierarchical correlation clusters in arbitrary subspaces.
class	SubspaceClusterModel<V extends RealVector<V,?>> todo arthur comment

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

private V	HierarchicalCorrelationCluster.centroid The centroid of this cluster.
private V	EMModel.mean

Methods in de.lmu.ifi.dbs.elki.algorithm.result.clustering that return types with arguments of type RealVector

private Database<RealVector>

SubspaceClusterMap.buildDerivatorDB(Database<ParameterizationFunction> database, Set<Integer> ids) Builds a database for the derivator consisting of the ids in the specified interval.

Uses of RealVector in de.lmu.ifi.dbs.elki.algorithm.result.clustering.biclustering

Classes in de.lmu.ifi.dbs.elki.algorithm.result.clustering.biclustering with type parameters of type RealVector

class	Bicluster<V extends RealVector<V,Double>> Wrapper class to provide the basic properties of a bicluster.
class	Biclustering<V extends RealVector<V,Double>> A Biclustering result holds a set of biclusters.

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

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

class

RealVector<V extends RealVector<V,N>,N extends Number> RealVector is an abstract super class for all feature vectors having real numbers as values.

Subclasses of RealVector in de.lmu.ifi.dbs.elki.data

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	ParameterizationFunction A parameterization function decribes all lines in a d-dimensional feature space intersecting in one point p.
class	SparseDoubleVector A SparseDoubleVector is to store real values approximately as double values.

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

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

class	AbstractCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,D extends CorrelationDistance<D>> Abstract super class for correlation based distance functions.
class	AbstractLocallyWeightedDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>> Abstract super class for locally weighted distance functions using a preprocessor to compute the local weight matrix.
class	DiSHDistanceFunction<V extends RealVector<V,?>,P extends Preprocessor<V>> Distance function used in the DiSH algorithm.
class	ERiCDistanceFunction<V extends RealVector<V,?>,P extends Preprocessor<V>> Provides a distance function for building the hierarchiy in the ERiC algorithm.
class	FractalDimensionBasedDistanceFunction<V extends RealVector<V,?>>
class	HiSCDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>> Distance function used in the HiSC algorithm.
class	KernelBasedLocallyWeightedDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>> Provides a kernel based locally weighted distance function.
class	LocallyWeightedDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>> Provides a locally weighted distance function.
class	PCABasedCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,D extends CorrelationDistance<D>> Provides the Correlation distance for real valued vectors.
class	PreferenceVectorBasedCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>> XXX unify CorrelationDistanceFunction and VarianceDistanceFunction
class	SubspaceDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,D extends SubspaceDistance<D>> Provides a distance function to determine a kind of correlation distance between two points, which is a pair consisting of the distance between the two subspaces spanned by the strong eigenvectors of the two points and the affine distance between the two subspaces.

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

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

class	ArbitraryKernelFunctionWrapper<O extends RealVector<O,?>> Provides a wrapper for arbitrary kernel functions whose kernel matrix has been precomputed.
class	KernelMatrix<O extends RealVector<O,?>> Provides a class for storing the kernel matrix and several extraction methods for convenience.

Method parameters in de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel with type arguments of type RealVector

static Matrix

KernelMatrix.centerKernelMatrix(KernelMatrix<? extends RealVector<?,? extends Number>> kernelMatrix) Centers the Kernel Matrix in Feature Space according to Smola et.

Uses of RealVector in de.lmu.ifi.dbs.elki.normalization

Classes in de.lmu.ifi.dbs.elki.normalization with type parameters of type RealVector

class

AttributeWiseRealVectorNormalization<V extends RealVector<V,?>> Class to perform and undo a normalization on real vectors with respect to given minimum and maximum in each dimension.

Methods in de.lmu.ifi.dbs.elki.normalization with parameters of type RealVector

private void

AttributeWiseRealVectorNormalization.determineMinMax(V[] featureVectors) Determines the minima and maxima values in each dimension of the given featureVectors.

Uses of RealVector in de.lmu.ifi.dbs.elki.parser

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

class

RealVectorLabelParser<V extends RealVector<V,?>> Provides a parser for parsing one point per line, attributes separated by whitespace.

Methods in de.lmu.ifi.dbs.elki.parser that return types with arguments of type RealVector

ParsingResult<RealVector>

RealVectorLabelTransposingParser.parse(InputStream in)

Uses of RealVector in de.lmu.ifi.dbs.elki.preprocessing

Classes in de.lmu.ifi.dbs.elki.preprocessing with type parameters of type RealVector

class	DiSHPreprocessor<V extends RealVector<V,N>,N extends Number> Preprocessor for DiSH preference vector assignment to objects of a certain database.
class	FourCPreprocessor<D extends Distance<D>,V extends RealVector<V,?>> Preprocessor for 4C local dimensionality and locally weighted matrix assignment to objects of a certain database.
class	FracClusPreprocessor<V extends RealVector<V,?>>
class	HiCOPreprocessor<V extends RealVector<V,?>> Abstract superclass for preprocessors for HiCO correlation dimension assignment to objects of a certain database.
class	HiSCPreprocessor<V extends RealVector<V,?>> Preprocessor for HiSC preference vector assignment to objects of a certain database.
class	KernelFourCPreprocessor<D extends Distance<D>,V extends RealVector<V,?>> Preprocessor for kernel 4C local dimensionality, neighbor objects and strong eigenvector matrix assignment to objects of a certain database.
class	KnnQueryBasedHiCOPreprocessor<V extends RealVector<V,?>> Computes the HiCO correlation dimension of objects of a certain database.
class	PreDeConPreprocessor<D extends Distance<D>,V extends RealVector<V,?>> Preprocessor for PreDeCon local dimensionality and locally weighted matrix assignment to objects of a certain database.
class	ProjectedDBSCANPreprocessor<D extends Distance<D>,V extends RealVector<V,?>> Abstract superclass for preprocessor of algorithms extending the ProjectedDBSCAN alghorithm.
class	RangeQueryBasedHiCOPreprocessor<V extends RealVector<V,?>> Computes the HiCO correlation dimension of objects of a certain database.

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

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

class

Subspace<V extends RealVector<V,?>> Represents a subspace of the original dataspace.

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

static <O extends RealVector<O,?>> O	Util.centroid(Database<O> database) Returns the centroid as a RealVector object of the specified database.
static <V extends RealVector<V,?>> V	Util.centroid(Database<V> database, Collection<Integer> ids) Returns the centroid as a RealVector object of the specified objects stored in the given database.
static <V extends RealVector<V,?>> V	Util.centroid(Database<V> database, Collection<Integer> ids, BitSet bitSet) Returns the centroid w.r.t. the dimensions specified by the given BitSet as a RealVector object of the specified objects stored in the given database.
static <O extends RealVector<O,?>> Matrix	Util.covarianceMatrix(Database<O> database) Determines the covariance matrix of the objects stored in the given database.
static <V extends RealVector<V,?>> Matrix	Util.covarianceMatrix(Database<V> database, Collection<Integer> ids) Determines the covariance matrix of the objects stored in the given database.
static <O extends RealVector<O,?>> double[]	Util.variances(Database<O> database) Determines the variances in each dimension of all objects stored in the given database.
static <V extends RealVector<V,?>> double[]	Util.variances(Database<V> database, Collection<Integer> ids) Determines the variances in each dimension of the specified objects stored in the given database.
static <V extends RealVector<V,?>> double[]	Util.variances(Database<V> database, V centroid, Collection<Integer> 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 RealVector

static double[]

Util.variances(Database<RealVector<?,?>> database, RealVector<?,?> centroid, Collection<Integer>[] 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 RealVector

static double[][]	Util.min_max(Database<RealVector<?,?>> database) Determines the minimum and maximum values in each dimension of all objects stored in the given database.
static double[]	Util.variances(Database<RealVector<?,?>> database, RealVector<?,?> centroid, Collection<Integer>[] ids) Determines the variances in each dimension of the specified objects stored in the given database.

Uses of RealVector in de.lmu.ifi.dbs.elki.varianceanalysis

Classes in de.lmu.ifi.dbs.elki.varianceanalysis with type parameters of type RealVector

class	GlobalPCA<O extends RealVector<O,?>> Computes the principal components for vector objects of a given database.
class	LinearLocalPCA<V extends RealVector<V,?>> Performs a linear local PCA based on the covariance matrices of given objects.
class	LocalKernelPCA<V extends RealVector<V,?>> Performs a local kernel PCA based on the kernel matrices of given objects.
class	LocalPCA<V extends RealVector<V,?>> LocalPCA is a super calss for PCA-algorithms considering only a local neighborhood.