Environment for
DeveLoping
KDD-Applications
Supported by Index-Structures

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

Packages that use RealVector
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.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.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.distance.distancefunction Distance functions for use within ELKI. 
de.lmu.ifi.dbs.elki.distance.distancefunction.correlation Distance functions using correlations. 
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace Distance functions based on subspaces. 
de.lmu.ifi.dbs.elki.distance.similarityfunction.kernel Kernel functions. 
de.lmu.ifi.dbs.elki.math.linearalgebra.pca Principal Component Analysis (PCA) and Eigenvector processing. 
de.lmu.ifi.dbs.elki.normalization Data normalization (and reconstitution) of data sets. 
de.lmu.ifi.dbs.elki.parser Parsers for different file formats and data types. 
de.lmu.ifi.dbs.elki.parser.meta MetaParsers for different file formats and data types. 
de.lmu.ifi.dbs.elki.preprocessing Preprocessors used for data preparation in a first step of various algorithms or distance and similarity measures. 
de.lmu.ifi.dbs.elki.utilities Utility and helper classes - commonly used data structures, output formatting, exceptions, ... 
 

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 quantitatively linear dependencies among attributes of a given dataset based on a linear correlation PCA.
 class MaterializeDistances<V extends RealVector<V,?>,D extends NumberDistance<D,N>,N extends Number>
           Algorithm to materialize all the distances in a data set.
 

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.correlation
 

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with type parameters of type RealVector
 class COPAC<V extends RealVector<V,?>>
          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.
 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, an algorithm to find clusters in high dimensional spaces.
 

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation declared as RealVector
(package private)  V ORCLUS.ORCLUSCluster.centroid
          The centroid of this cluster.
 

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,?>>
          

Provides the PROCLUS algorithm, an algorithm to find subspace clusters in high dimensional spaces.

 class ProjectedClustering<V extends RealVector<V,?>>
          Abstract superclass for projected clustering algorithms, like PROCLUS and ORCLUS.
 

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace declared as RealVector
(package private)  V PROCLUS.PROCLUSCluster.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.outlier
 

Classes in de.lmu.ifi.dbs.elki.algorithm.outlier with type parameters of type RealVector
 class ABOD<V extends RealVector<V,?>>
          Angle-Based Outlier Detection Outlier detection using variance analysis on angles, especially for high dimensional data sets.
 class SOD<V extends RealVector<V,Double>,D extends Distance<D>>
           
 class SODModel<O extends RealVector<O,Double>>
           
 

Fields in de.lmu.ifi.dbs.elki.algorithm.outlier declared as RealVector
private  O SODModel.center
           
 

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

Classes in de.lmu.ifi.dbs.elki.algorithm.statistics with type parameters of type RealVector
 class DistanceStatisticsWithClasses<V extends RealVector<V,?>,D extends NumberDistance<D,?>>
          Algorithm to gather statistics over the distance distribution in the data set.
 class EvaluateRankingQuality<V extends RealVector<V,?>,D extends NumberDistance<D,?>>
          Evaluate a distance function with respect to kNN queries.
 class RankingQualityHistogram<V extends RealVector<V,?>,D extends NumberDistance<D,?>>
          Evaluate a distance function with respect to kNN queries.
 

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.
 class Subspace<V extends RealVector<V,?>>
          Represents a subspace of the original data space.
 

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 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.
 

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

Classes in de.lmu.ifi.dbs.elki.data.model with type parameters of type RealVector
 class Bicluster<V extends RealVector<V,Double>>
          Wrapper class to provide the basic properties of a bicluster.
 class BiclusterWithInverted<V extends RealVector<V,Double>>
          This code was factored out of the Bicluster class, since not all biclusters have inverted rows.
 class CorrelationAnalysisSolution<V extends RealVector<V,?>>
          A solution of correlation analysis is a matrix of equations describing the dependencies.
 class CorrelationModel<V extends RealVector<V,?>>
          Cluster model using a filtered PCA result and an centroid.
 class EMModel<V extends RealVector<V,?>>
          Cluster model of an EM cluster, providing a mean and a full covariance Matrix.
 

Fields in de.lmu.ifi.dbs.elki.data.model declared as RealVector
private  V CorrelationModel.centroid
          The centroid of this cluster.
private  V EMModel.mean
          Cluster mean
 

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 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 KernelBasedLocallyWeightedDistanceFunction<V extends RealVector<V,?>,P extends Preprocessor<V>>
          Provides a kernel based locally weighted distance function.
 class LocallyWeightedDistanceFunction<V extends RealVector<V,?>,P extends Preprocessor<V>>
          Provides a locally weighted distance function.
 

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

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation with type parameters of type RealVector
 class AbstractCorrelationDistanceFunction<V extends RealVector<V,?>,P extends Preprocessor<V>,D extends CorrelationDistance<D>>
          Abstract super class for correlation based distance functions.
 class AbstractPreferenceVectorBasedCorrelationDistanceFunction<V extends RealVector<V,?>,P extends PreferenceVectorPreprocessor<V>>
          Abstract super class for all preference vector based correlation distance functions.
 class ERiCDistanceFunction<V extends RealVector<V,?>,P extends Preprocessor<V>>
          Provides a distance function for building the hierarchiy in the ERiC algorithm.
 class PCABasedCorrelationDistanceFunction<V extends RealVector<V,?>,P extends HiCOPreprocessor<V>,D extends CorrelationDistance<D>>
          Provides the correlation distance for real valued vectors.
 

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

Classes in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace with type parameters of type RealVector
 class DiSHDistanceFunction<V extends RealVector<V,?>,P extends PreferenceVectorPreprocessor<V>>
          Distance function used in the DiSH algorithm.
 class HiSCDistanceFunction<V extends RealVector<V,?>,P extends PreferenceVectorPreprocessor<V>>
          Distance function used in the HiSC algorithm.
 class SubspaceDistanceFunction<V extends RealVector<V,?>,P extends Preprocessor<V>>
          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.math.linearalgebra.pca
 

Classes in de.lmu.ifi.dbs.elki.math.linearalgebra.pca with type parameters of type RealVector
 class CovarianceMatrixBuilder<V extends RealVector<V,?>,D extends NumberDistance<D,?>>
          Abstract class with the task of computing a Covariance matrix to be used in PCA.
 class KernelCovarianceMatrixBuilder<V extends RealVector<V,?>,D extends NumberDistance<D,?>>
          Kernel Covariance Matrix Builder.
 class PCAFilteredRunner<V extends RealVector<V,?>,D extends NumberDistance<D,?>>
          PCA runner that will do dimensionality reduction.
 class PCARunner<V extends RealVector<V,?>,D extends NumberDistance<D,?>>
          Class to run PCA on given data.
 class StandardCovarianceMatrixBuilder<V extends RealVector<V,?>,D extends NumberDistance<D,?>>
          Class for building a "traditional" covariance matrix.
 class WeightedCovarianceMatrixBuilder<V extends RealVector<V,?>,D extends NumberDistance<D,?>>
          CovarianceMatrixBuilder with weights.
 

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 AttributeWiseMinMaxNormalization<V extends RealVector<V,?>>
          Class to perform and undo a normalization on real vectors with respect to given minimum and maximum in each dimension.
 class AttributeWiseVarianceNormalization<V extends RealVector<V,?>>
          Class to perform and undo a normalization on real vectors with respect to given mean and standard deviation in each dimension.
 

Methods in de.lmu.ifi.dbs.elki.normalization with parameters of type RealVector
private  void AttributeWiseVarianceNormalization.determineMeanVariance(V[] featureVectors)
          Determines the mean and standard deviations in each dimension of the given featureVectors.
private  void AttributeWiseMinMaxNormalization.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<?,?>>
           Provides a parser for parsing one point per line, attributes separated by whitespace.
 

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

Classes in de.lmu.ifi.dbs.elki.parser.meta with type parameters of type RealVector
 class ProjectionParser<V extends RealVector<V,?>>
          A ProjectionParser projects the ParsingResult of its base parser onto a subspace specified by a BitSet.
 class RandomProjectionParser<V extends RealVector<V,?>>
          A RandomProjectionParser selects a subset of attributes randomly for projection of a ParsingResult.
 

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 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 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 algorithm.
 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
 

Methods in de.lmu.ifi.dbs.elki.utilities with type parameters of type RealVector
static
<O extends RealVector<O,?>>
O
DatabaseUtil.centroid(Database<O> database)
          Returns the centroid as a RealVector object of the specified database.
static
<V extends RealVector<V,?>>
V
DatabaseUtil.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
DatabaseUtil.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
<V extends RealVector<V,?>>
V
DatabaseUtil.centroid(Database<V> database, Iterator<Integer> iter, 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
DatabaseUtil.covarianceMatrix(Database<O> database)
          Determines the covariance matrix of the objects stored in the given database.
static
<O extends RealVector<O,?>>
Matrix
DatabaseUtil.covarianceMatrix(Database<O> database, O centroid)
           Determines the covariance matrix of the objects stored in the given database w.r.t. the given centroid.
static
<V extends RealVector<V,?>>
Matrix
DatabaseUtil.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[]
DatabaseUtil.variances(Database<O> database)
          Determines the variances in each dimension of all objects stored in the given database.
static
<V extends RealVector<V,?>>
double[]
DatabaseUtil.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[]
DatabaseUtil.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[] DatabaseUtil.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[][] DatabaseUtil.min_max(Database<RealVector<?,?>> database)
          Determines the minimum and maximum values in each dimension of all objects stored in the given database.
static double[] DatabaseUtil.variances(Database<RealVector<?,?>> database, RealVector<?,?> centroid, Collection<Integer>[] ids)
          Determines the variances in each dimension of the specified objects stored in the given database.
 


Release 0.2 (2009-07-06_1820)