A B C D E F G H I J K L M N O P Q R S T U V W X Y Z _

E

e - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenvalueDecomposition

Arrays for internal storage of eigenvalues.

e - Variable in class de.lmu.ifi.dbs.elki.math.statistics.MultipleLinearRegression

The (n x 1) - vector holding the estimated residuals (e1, ..., en)^T.

e_czech - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredResult

The selection matrix of the strong eigenvectors.

e_hat - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredResult

The selection matrix of the weak eigenvectors.

eclass - Variable in class de.lmu.ifi.dbs.elki.index.tree.AbstractNode

Entry class.

EDRDistanceFunction<V extends NumberVector<V,?>> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries

Provides the Edit Distance on Real Sequence distance for NumberVectors.

EDRDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.EDRDistanceFunction

Provides a Edit Distance on Real Sequence distance function that can compute the Dynamic Time Warping distance (that is a DoubleDistance) for NumberVectors.

eig() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix

Eigenvalue Decomposition

EigenPair - Class in de.lmu.ifi.dbs.elki.math.linearalgebra

Helper class which encapsulates an eigenvector and its corresponding eigenvalue.

EigenPair(Matrix, double) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenPair

Creates a new EigenPair object.

EIGENPAIR_FILTER_ABSOLUTE - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.LimitEigenPairFilter

OptionID for LimitEigenPairFilter.ABSOLUTE_FLAG

EIGENPAIR_FILTER_ALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PercentageEigenPairFilter

OptionID for PercentageEigenPairFilter.ALPHA_PARAM

EIGENPAIR_FILTER_COMPOSITE_LIST - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.CompositeEigenPairFilter

OptionID for CompositeEigenPairFilter.FILTERS_PARAM

EIGENPAIR_FILTER_DELTA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.LimitEigenPairFilter

OptionID for LimitEigenPairFilter.DELTA_PARAM

EIGENPAIR_FILTER_N - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.FirstNEigenPairFilter

OptionID for FirstNEigenPairFilter.N_PARAM

EIGENPAIR_FILTER_PALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.ProgressiveEigenPairFilter

OptionID for ProgressiveEigenPairFilter.PALPHA_PARAM

EIGENPAIR_FILTER_PARAM - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredRunner

Parameter to specify the filter for determination of the strong and weak eigenvectors, must be a subclass of EigenPairFilter.

EIGENPAIR_FILTER_RALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.RelativeEigenPairFilter

OptionID for RelativeEigenPairFilter.RALPHA_PARAM

EIGENPAIR_FILTER_WALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.WeakEigenPairFilter

OptionID for WeakEigenPairFilter.WALPHA_PARAM and ProgressiveEigenPairFilter.WALPHA_PARAM and SignificantEigenPairFilter.WALPHA_PARAM

EigenPairFilter - Interface in de.lmu.ifi.dbs.elki.math.linearalgebra.pca

The eigenpair filter is used to filter eigenpairs (i.e. eigenvectors and their corresponding eigenvalues) which are a result of a Variance Analysis Algorithm, e.g.

eigenPairFilter - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredRunner

Holds the instance of the EigenPairFilter specified by PCAFilteredRunner.EIGENPAIR_FILTER_PARAM.

eigenPairs - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAResult

The eigenpairs in decreasing order.

eigenPairs - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.SortedEigenPairs

The array of eigenpairs.

eigenvalue - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenPair

The corresponding eigenvalue.

EigenvalueDecomposition - Class in de.lmu.ifi.dbs.elki.math.linearalgebra

Eigenvalues and eigenvectors of a real matrix.

EigenvalueDecomposition(Matrix) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenvalueDecomposition

Check for symmetry, then construct the eigenvalue decomposition

eigenvalues - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAResult

The eigenvalues in decreasing order.

eigenValues() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.SortedEigenPairs

Returns the sorted eigenvalues.

eigenvector - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenPair

The eigenvector as a matrix.

eigenvectors - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAResult

The eigenvectors in decreasing order to their corresponding eigenvalues.

eigenVectors() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.SortedEigenPairs

Returns the sorted eigenvectors.

eigenVectors(int) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.SortedEigenPairs

Returns the first n sorted eigenvectors as a matrix.

elements - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix

Array for internal storage of elements.

ELKI_PROPERTIES - Static variable in class de.lmu.ifi.dbs.elki.properties.Properties

The Properties for ELKI.

ElkiLogRecord - Class in de.lmu.ifi.dbs.elki.logging

Base LogRecord class used in ELKI.

ElkiLogRecord(Level, String) - Constructor for class de.lmu.ifi.dbs.elki.logging.ElkiLogRecord

Constructor.

EM<V extends RealVector<V,?>> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering

Provides the EM algorithm (clustering by expectation maximization).

EM() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.EM

Provides the EM algorithm (clustering by expectation maximization), adding parameters EM.K_PARAM and EM.DELTA_PARAM to the option handler additionally to parameters of super class.

EMModel<V extends RealVector<V,?>> - Class in de.lmu.ifi.dbs.elki.data.model

Cluster model of an EM cluster, providing a mean and a full covariance Matrix.

EMModel(V, Matrix) - Constructor for class de.lmu.ifi.dbs.elki.data.model.EMModel

Constructor.

EMPTY_ENUMERATION - Variable in class de.lmu.ifi.dbs.elki.index.tree.BreadthFirstEnumeration

Represents an empty enumeration.

EMPTY_PAGE - Static variable in class de.lmu.ifi.dbs.elki.persistent.OnDiskArrayPageFile

Indicates an empty page.

EMPTY_PAGE - Static variable in class de.lmu.ifi.dbs.elki.persistent.PersistentPageFile

Indicates an empty page.

emptyPages - Variable in class de.lmu.ifi.dbs.elki.persistent.PageFile

A stack holding the empty page ids.

Enlargement<E extends SpatialEntry> - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.util

Encapsulates the parameters for enlargement of nodes after insertion of new objects.

Enlargement(TreeIndexPathComponent<E>, double, double, double) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.util.Enlargement

Creates an new Enlargement object with the specified parameters.

entries - Variable in class de.lmu.ifi.dbs.elki.index.tree.AbstractNode

The entries (children) of this node.

entry - Variable in class de.lmu.ifi.dbs.elki.index.tree.DistanceEntry

The entry of the Index.

Entry - Interface in de.lmu.ifi.dbs.elki.index.tree

Defines the requirements for an entry in an index structure.

entry - Variable in class de.lmu.ifi.dbs.elki.index.tree.TreeIndexPathComponent

The entry of this component.

entry - Variable in class de.lmu.ifi.dbs.elki.properties.PropertyDescription

Entry of property.

entry1 - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.DeLiClu.SpatialObjectPair

The first entry of this pair.

entry2 - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.DeLiClu.SpatialObjectPair

The second entry of this pair.

epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN

Holds the value of DBSCAN.EPSILON_PARAM.

epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.OPTICS

Hold the value of OPTICS.EPSILON_PARAM.

epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.ProjectedDBSCAN

Holds the value of ProjectedDBSCAN.EPSILON_PARAM.

epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.SNNClustering

Holds the value of SNNClustering.EPSILON_PARAM.

epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH

Holds the value of DiSH.EPSILON_PARAM.

epsilon - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.AbstractPreferenceVectorBasedCorrelationDistanceFunction

Holds the value of AbstractPreferenceVectorBasedCorrelationDistanceFunction.EPSILON_PARAM.

epsilon - Variable in class de.lmu.ifi.dbs.elki.preprocessing.DiSHPreprocessor

The epsilon value for each dimension;

epsilon - Variable in class de.lmu.ifi.dbs.elki.preprocessing.ProjectedDBSCANPreprocessor

Contains the value of parameter epsilon;

epsilon - Variable in class de.lmu.ifi.dbs.elki.preprocessing.RangeQueryBasedHiCOPreprocessor

Epsilon.

EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN

OptionID for DBSCAN.EPSILON_PARAM

EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.OPTICS

OptionID for OPTICS.EPSILON_PARAM

EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.ProjectedDBSCAN

OptionID for ProjectedDBSCAN.EPSILON_PARAM

EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.SNNClustering

OptionID for SNNClustering.EPSILON_PARAM

EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH

OptionID for DiSH.EPSILON_PARAM

EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.AbstractPreferenceVectorBasedCorrelationDistanceFunction

OptionID for AbstractPreferenceVectorBasedCorrelationDistanceFunction.EPSILON_PARAM

EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.preprocessing.DiSHPreprocessor

OptionID for DiSHPreprocessor.EPSILON_PARAM

EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.preprocessing.RangeQueryBasedHiCOPreprocessor

OptionID for RangeQueryBasedHiCOPreprocessor.EPSILON_PARAM

EPSILON_PARAM - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN

Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to the distance function specified.

EPSILON_PARAM - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.OPTICS

Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to the distance function specified.

EPSILON_PARAM - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.ProjectedDBSCAN

Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to LocallyWeightedDistanceFunction.

EPSILON_PARAM - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.SNNClustering

Parameter to specify the minimum SNN density, must be an integer greater than 0.

EPSILON_PARAM - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH

Parameter that specifies the maximum radius of the neighborhood to be considered in each dimension for determination of the preference vector, must be a double equal to or greater than 0.

EPSILON_PARAM - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.AbstractPreferenceVectorBasedCorrelationDistanceFunction

Parameter to specify the maximum distance between two vectors with equal preference vectors before considering them as parallel, must be a double equal to or greater than 0.

EPSILON_PARAM - Variable in class de.lmu.ifi.dbs.elki.preprocessing.DiSHPreprocessor

Parameter Epsilon.

EPSILON_PARAM - Static variable in class de.lmu.ifi.dbs.elki.preprocessing.ProjectedDBSCANPreprocessor

Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to LocallyWeightedDistanceFunction.

EPSILON_PARAM - Variable in class de.lmu.ifi.dbs.elki.preprocessing.RangeQueryBasedHiCOPreprocessor

Parameter to specify the epsilon used in the preprocessor Key: -preprocessor.epsilon

equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.CASHInterval

equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.OPTICS.COEntry

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.data.BitVector

Indicates whether some other object is "equal to" this BitVector.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.data.ClassLabel

Any ClassLabel should ensure a natural ordering that is consistent with equals.

equals(Object) - Method in interface de.lmu.ifi.dbs.elki.data.DatabaseObject

Equality of DatabaseObject should be defined by their values regardless of their id.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.data.KNNList

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.data.NumberVector

An Object obj is equal to this NumberVector if it is an instance of the same runtime class and is of the identical dimensionality and the values of this NumberVector are equal to the values of obj in all dimensions, respectively.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.data.RationalNumber

Two RationalNumbers are considered to be equal if both denominators and numerators are equal, respectively.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.data.SimpleClassLabel

Any ClassLabel should ensure a natural ordering that is consistent with equals.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.AbstractDistance

Returns true if this == o has the value true or o is not null and o is of the same class as this instance and this.compareTo(o) is 0, false otherwise.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.AbstractEntry

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.AbstractNode

Returns true if this == o has the value true or o is not null and o is of the same class as this instance and super.equals(o) returns true and both nodes are of the same type (leaf node or directory node) and have contain the same entries, false otherwise.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.ApproximationLine

Returns true if this object is the same as the o argument; false otherwise.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPDirectoryEntry

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPLeafEntry

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxDirectoryEntry

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxLeafEntry

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabDirectoryEntry

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabLeafEntry

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.MTreeDirectoryEntry

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.MTreeLeafEntry

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNDirectoryEntry

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNLeafEntry

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.TreeIndexPath

Returns true if this == o has the value true or o is not null and o is of the same class as this instance and the two index paths are of the same length, and contain the same components (.equals), false otherwise.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.TreeIndexPathComponent

Returns true if this == o has the value true or o is not null and o is of the same class as this instance and if the entry of this component equals the entry of the o argument, false otherwise.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix

equals(Object) - Method in class de.lmu.ifi.dbs.elki.persistent.AbstractPage

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.result.ClusterOrderEntry

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.ConstantObject

equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.heap.DefaultIdentifiable

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.HyperBoundingBox

equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.DoubleParameter

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.DoubleDoublePair

Trivial equals implementation

equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.DoubleIntPair

Trivial equals implementation

equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.IntDoublePair

Trivial equals implementation

equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.IntIntPair

Trivial equals implementation

equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.Pair

Simple equals statement.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.Triple

Canonical equals function

EqualSizeGlobalConstraint - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints

Global parameter constraint defining that a number of list parameters (ListParameter) must have equal list sizes.

EqualSizeGlobalConstraint(List<ListParameter<?>>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.EqualSizeGlobalConstraint

Creates a global parameter constraint for testing if a number of list parameters have equal list sizes.

EqualStringConstraint - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints

Represents a parameter constraint for testing if the string value of the string parameter (PatternParameter) to be tested is equal to the specified constraint-strings.

EqualStringConstraint(String[]) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.EqualStringConstraint

Creates an Equal-To-String parameter constraint.

equationsToString(String, int) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem

Returns a string representation of this equation system.

equationsToString(int) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem

Returns a string representation of this equation system.

erf(double) - Static method in class de.lmu.ifi.dbs.elki.math.ErrorFunctions

Error function for Gaussian distributions = Normal distributions.

erfc(double) - Static method in class de.lmu.ifi.dbs.elki.math.ErrorFunctions

Complementary error function for Gaussian distributions = Normal distributions.

ErfcStddevWeight - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions

Gaussian Error Function Weight function, scaled using stddev.

ErfcStddevWeight() - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions.ErfcStddevWeight

ErfcWeight - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions

Gaussian Error Function Weight function, scaled such that the result it 0.1 at distance == max erfc(1.1630871536766736 * distance / max) The value of 1.1630871536766736 is erfcinv(0.1), to achieve the intended scaling.

ErfcWeight() - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions.ErfcWeight

ERiC<V extends RealVector<V,?>> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation

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.

ERiC() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ERiC

Performs the COPAC algorithm on the data and builds a hierarchy of correlation clusters that allows multiple inheritance from the clustering result.

ERiCDistanceFunction<V extends RealVector<V,?>,P extends Preprocessor<V>> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation

Provides a distance function for building the hierarchiy in the ERiC algorithm.

ERiCDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.ERiCDistanceFunction

Provides a distance function for the ERiC algorithm, adding parameters ERiCDistanceFunction.DELTA_PARAM and {#TAU_PARAM} to the option handler additionally to parameters of super class.

ERPDistanceFunction<V extends NumberVector<V,?>> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries

Provides the Edit Distance With Real Penalty distance for NumberVectors.

ERPDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.ERPDistanceFunction

Provides a Edit Distance With Real Penalty distance function that can compute the Dynamic Time Warping distance (that is a DoubleDistance) for NumberVectors.

err - Variable in class de.lmu.ifi.dbs.elki.logging.CLISmartHandler

Output stream for error output.

errformat - Variable in class de.lmu.ifi.dbs.elki.logging.CLISmartHandler

Formatter for error messages

error(String, Throwable) - Method in class de.lmu.ifi.dbs.elki.logging.Logging

Log a message at the 'severe' level.

error(String) - Method in class de.lmu.ifi.dbs.elki.logging.Logging

Log a message at the 'severe' level.

ErrorFunctions - Class in de.lmu.ifi.dbs.elki.math

Some mathematical error functions.

ErrorFunctions() - Constructor for class de.lmu.ifi.dbs.elki.math.ErrorFunctions

errorVector(V) - Method in class de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution

Returns the error vectors after projection.

errorVectors(V) - Method in class de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution

Returns the error vectors after projection.

errorVectors(Matrix) - Method in class de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution

Returns the error vectors after projection.

estimateY(Matrix) - Method in class de.lmu.ifi.dbs.elki.math.statistics.MultipleLinearRegression

Performes an estimatation of y on the specified matrix.

estimateY(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.PolynomialRegression

Performes an estimatation of y on the specified x value.

euclideanDistance(V, V) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.PCABasedCorrelationDistanceFunction

Computes the Euclidean distance between the given two vectors.

EuclideanDistanceFunction<V extends NumberVector<V,?>> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction

Provides the Euclidean distance for NumberVectors.

EuclideanDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.EuclideanDistanceFunction

Provides a Euclidean distance function that can compute the Euclidean distance (that is a DoubleDistance) for NumberVectors.

euclideanNorm(int) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix

Returns the euclidean norm of the col column.

euclideanValue - Variable in class de.lmu.ifi.dbs.elki.distance.CorrelationDistance

The euclidean distance.

eval(double, double[]) - Method in interface de.lmu.ifi.dbs.elki.math.linearalgebra.fitting.FittingFunction

Compute value at position x as well as gradients for the parameters

eval(double, double[]) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.fitting.GaussianFittingFunction

compute the mixture of Gaussians at the given position

evaluateClusters(Map<Integer, PROCLUS<V>.PROCLUSCluster>, Map<Integer, Set<Integer>>, Database<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS

Evaluates the quality of the clusters.

EvaluateRankingQuality<V extends RealVector<V,?>,D extends NumberDistance<D,?>> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics

Evaluate a distance function with respect to kNN queries.

EvaluateRankingQuality() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRankingQuality

Empty constructor.

exactGaussElimination() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix

Perform an exact Gauss-elimination of this Matrix using RationalNumbers to yield highest possible accuracy.

exactGaussElimination(RationalNumber[][]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix

Perform recursive Gauss-elimination on the given matrix of RationalNumbers.

exactGaussJordanElimination() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix

Returns a matrix derived by Gauss-Jordan-elimination using RationalNumbers for the transformations.

exactMinMax(Database<V>, DistanceFunction<V, D>) - Method in class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceStatisticsWithClasses

exception(String, Throwable) - Method in class de.lmu.ifi.dbs.elki.logging.AbstractLoggable

Log an exception at SEVERE level.

exception(String, Throwable) - Method in class de.lmu.ifi.dbs.elki.logging.Logging

Log a message with exception at the 'severe' level.

exception(Throwable) - Method in class de.lmu.ifi.dbs.elki.logging.Logging

Log an exception at the 'severe' level.

exception(Throwable) - Static method in class de.lmu.ifi.dbs.elki.logging.LoggingUtil

Static version to log a severe exception.

exception(String, Throwable) - Static method in class de.lmu.ifi.dbs.elki.logging.LoggingUtil

Static version to log a severe exception.

ExceptionMessages - Interface in de.lmu.ifi.dbs.elki.utilities

Interface to collect exception messages that are used in several cases.

executeResize(double) - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.LazyCanvasResizer

Callback function that needs to be overridden with actual implementations.

expandCluster(Database<O>, Integer, FiniteProgress, IndefiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN

DBSCAN-function expandCluster.

expandCluster(Database<V>, Integer, FiniteProgress, IndefiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.ProjectedDBSCAN

ExpandCluster function of DBSCAN.

expandCluster(Database<O>, Integer, FiniteProgress, IndefiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.SNNClustering

DBSCAN-function expandCluster adapted to SNN criterion.

expandClusterOrder(Database<O>, Integer, FiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.OPTICS

OPTICS-function expandClusterOrder.

expandDirNodes(SpatialDistanceFunction<O, D>, DeLiCluNode, DeLiCluNode) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.DeLiClu

Expands the specified directory nodes.

expanded - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTree

Holds the ids of the expanded nodes.

expandLeafNodes(SpatialDistanceFunction<O, D>, DeLiCluNode, DeLiCluNode, AnnotationResult<KNNList<D>>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.DeLiClu

Expands the specified directory nodes.

expandNodes(DeLiCluTree<O>, SpatialDistanceFunction<O, D>, DeLiClu<O, D>.SpatialObjectPair, AnnotationResult<KNNList<D>>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.DeLiClu

Expands the spatial nodes of the specified pair.

expectationOfMixture(Database<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.EM

The expectation value of the current mixture of distributions.

expectationOfVariance - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.SODModel

explain(double) - Method in interface de.lmu.ifi.dbs.elki.data.synthetic.bymodel.distribution.Distribution

Return the density of an existing value

explain(double) - Method in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.distribution.NormalDistribution

Return the PDF of the generators distribution

explain(double) - Method in class de.lmu.ifi.dbs.elki.data.synthetic.bymodel.distribution.UniformDistribution

Return the PDF of the generators distribution

explainedVariance - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredResult

The amount of Variance explained by strong Eigenvalues

ExponentialStddevWeight - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions

Exponential Weight function, scaled such that the result it 0.1 at distance == max stddev * exp(-.5 * distance/stddev) This is similar to the Gaussian weight function, except distance/stddev is not squared.

ExponentialStddevWeight() - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions.ExponentialStddevWeight

ExponentialWeight - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions

Exponential Weight function, scaled such that the result it 0.1 at distance == max exp(-2.3025850929940455 * distance/max) This is similar to the Gaussian weight function, except distance/max is not squared

ExponentialWeight() - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions.ExponentialWeight

EXTENSION - Static variable in class de.lmu.ifi.dbs.elki.result.textwriter.MultipleFilesOutput

File name extension.

EXTERNAL_ID - Static variable in class de.lmu.ifi.dbs.elki.database.AssociationID

The association id to associate an external id to an object.

EXTERNAL_ID_INDEX_ID - Static variable in class de.lmu.ifi.dbs.elki.database.connection.AbstractDatabaseConnection

OptionID for AbstractDatabaseConnection.EXTERNAL_ID_INDEX_PARAM

EXTERNAL_ID_INDEX_PARAM - Variable in class de.lmu.ifi.dbs.elki.database.connection.AbstractDatabaseConnection

Optional parameter that specifies the index of the label to be used as an external id, must be an integer equal to or greater than 0.

externalIDIndex - Variable in class de.lmu.ifi.dbs.elki.database.connection.AbstractDatabaseConnection

Holds the value of AbstractDatabaseConnection.EXTERNAL_ID_INDEX_PARAM.

externalizableSize() - Method in class de.lmu.ifi.dbs.elki.distance.BitDistance

Returns the number of Bytes this distance uses if it is written to an external file.

externalizableSize() - Method in class de.lmu.ifi.dbs.elki.distance.CorrelationDistance

Returns the number of Bytes this distance uses if it is written to an external file.

externalizableSize() - Method in interface de.lmu.ifi.dbs.elki.distance.Distance

Returns the number of Bytes this distance uses if it is written to an external file.

externalizableSize() - Method in class de.lmu.ifi.dbs.elki.distance.DoubleDistance

Returns the number of Bytes this distance uses if it is written to an external file.

externalizableSize() - Method in class de.lmu.ifi.dbs.elki.distance.FloatDistance

Returns the number of Bytes this distance uses if it is written to an external file.

externalizableSize() - Method in class de.lmu.ifi.dbs.elki.distance.IntegerDistance

Returns the number of Bytes this distance uses if it is written to an external file.

externalizableSize() - Method in class de.lmu.ifi.dbs.elki.distance.PreferenceVectorBasedCorrelationDistance

Returns the number of Bytes this distance uses if it is written to an external file.

externalizableSize() - Method in class de.lmu.ifi.dbs.elki.distance.SubspaceDistance

Returns the number of Bytes this distance uses if it is written to an external file.

ExternalObject - Class in de.lmu.ifi.dbs.elki.data

Provides an id referencing an external data object.

ExternalObject(Integer) - Constructor for class de.lmu.ifi.dbs.elki.data.ExternalObject

Creates a new ExternalObject with the specified id.

extractClusters(Database<V>, DiSHDistanceFunction<V, DiSHPreprocessor<V, ?>>, ClusterOrderResult<PreferenceVectorBasedCorrelationDistance>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH

Extracts the clusters from the cluster order.

extractCorrelationClusters(Database<V>, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ERiC

Extracts the correlation clusters and noise from the copac result and returns a mapping of correlation dimension to maps of clusters within this correlation dimension.

extraIntegrityChecks - Static variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree

extraIntegrityChecks - Static variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree

extremum_alpha_n(int, double[]) - Method in class de.lmu.ifi.dbs.elki.data.ParameterizationFunction

Determines the value for alpha_n where this function has a (local) extremum.

extremumType - Variable in class de.lmu.ifi.dbs.elki.data.ParameterizationFunction

Holds the type of the global extremum.

extremumType(int, double[], HyperBoundingBox) - Method in class de.lmu.ifi.dbs.elki.data.ParameterizationFunction

Returns the type of the extremum at the specified alpha values.