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.geodesy.AbstractEarthModel

Derived model parameters: e and e squared.

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 - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.AttributeModifier

Provides the attribute to be modified.

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.

EARTH_RADIUS - Static variable in class de.lmu.ifi.dbs.elki.math.geodesy.SphericalCosineEarthModel

Earth radius approximation in m.

EARTH_RADIUS - Static variable in class de.lmu.ifi.dbs.elki.math.geodesy.SphericalHaversineEarthModel

Earth radius approximation in m.

EARTH_RADIUS - Static variable in class de.lmu.ifi.dbs.elki.math.geodesy.SphericalVincentyEarthModel

Earth radius approximation in m.

EarthModel - Interface in de.lmu.ifi.dbs.elki.math.geodesy

API for handling different earth models.

ecefToLatDeg(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel

ecefToLatDeg(double, double, double) - Method in interface de.lmu.ifi.dbs.elki.math.geodesy.EarthModel

Convert a 3D coordinate pair to the corresponding latitude.

ecefToLatLngDegHeight(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel

ecefToLatLngDegHeight(double, double, double) - Method in interface de.lmu.ifi.dbs.elki.math.geodesy.EarthModel

Convert a 3D coordinate pair to the corresponding latitude, longitude and height.

ecefToLatLngRadHeight(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel

ecefToLatLngRadHeight(double, double, double) - Method in interface de.lmu.ifi.dbs.elki.math.geodesy.EarthModel

Convert a 3D coordinate pair to the corresponding latitude, longitude and height.

ecefToLatRad(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel

ecefToLatRad(double, double, double) - Method in interface de.lmu.ifi.dbs.elki.math.geodesy.EarthModel

Convert a 3D coordinate pair to the corresponding latitude.

ecefToLatRad(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.SphericalCosineEarthModel

ecefToLatRad(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.SphericalHaversineEarthModel

ecefToLatRad(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.SphericalVincentyEarthModel

ecefToLngDeg(double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel

ecefToLngDeg(double, double) - Method in interface de.lmu.ifi.dbs.elki.math.geodesy.EarthModel

Convert a 3D coordinate pair to the corresponding longitude.

ecefToLngRad(double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel

ecefToLngRad(double, double) - Method in interface de.lmu.ifi.dbs.elki.math.geodesy.EarthModel

Convert a 3D coordinate pair to the corresponding longitude.

Eclat - Class in de.lmu.ifi.dbs.elki.algorithm.itemsetmining

Eclat is a depth-first discovery algorithm for mining frequent itemsets.

Eclat(double, int, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.Eclat

Constructor.

Eclat.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.itemsetmining

Parameterization class.

Eclat.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.Eclat.Parameterizer

edit - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.ClusterContingencyTable

Edit-Distance measures

EDIT_CLEAR - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon

EDIT_FIND - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon

EDIT_REDO - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon

EDIT_UNDO - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon

EditDistance - Class in de.lmu.ifi.dbs.elki.evaluation.clustering

Edit distance measures.

EditDistance(ClusterContingencyTable) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance

editDistanceFirst() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance

Get the editing distance to transform second clustering to first clustering (normalized, 0 = unequal)

editDistanceSecond() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance

Get the editing distance to transform second clustering to first clustering (normalized, 0 = unequal)

editFirst - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance

Edit operations for first clustering to second clustering.

editItem - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.ResultWindow.DynamicMenu

The "tabular edit" item.

editOperationsBaseline - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance

Baseline for edit operations

editOperationsBaseline() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance

Get the baseline editing Operations ( = total Objects)

editOperationsFirst() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance

Get the editing operations required to transform first clustering to second clustering

editOperationsSecond() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance

Get the editing operations required to transform second clustering to first clustering

editSecond - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance

Edit operations for second clustering to first clustering.

EDRDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries

Edit Distance on Real Sequence distance for numerical vectors.

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

Constructor.

EDRDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries

Parameterization class.

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

effectiveBandSize(int, int) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.AbstractEditDistanceFunction

Compute the effective band size.

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

Helper class which encapsulates an eigenvector and its corresponding eigenvalue.

EigenPair(Vector, 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

"absolute" Flag

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

The list of filters to use.

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

Parameter delta

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

Paremeter n

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

Parameter progressive alpha.

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

Parameter relative alpha.

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

OptionID for the weak alpha value of WeakEigenPairFilter, ProgressiveEigenPairFilter and SignificantEigenPairFilter

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.Parameterizer.PCA_EIGENPAIR_FILTER.

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

Holds the instance of the EigenPairFilter specified by PCAFilteredRunner.Parameterizer.PCA_EIGENPAIR_FILTER.

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.

element - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea

Our element node.

elementCoordinatesFromEvent(Element, Event) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPlot

Convert screen coordinates to element coordinates.

elementCoordinatesFromEvent(Document, Element, Event) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGUtil

Convert the coordinates of an DOM Event from screen into element coordinates.

elementLine - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance

The line element

elementPoint - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance

The drag handle element

elements - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.MultivariateGaussianModel

Matrix element reference.

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

The covariance matrix.

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

Array for internal storage of elements.

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

Array for internal storage of elements.

elems - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy

All elements, in insertion order (and will not fail badly if concurrent insertions happen).

elemText - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance

The label element

ELKILauncher - Class in de.lmu.ifi.dbs.elki.application

Class to launch ELKI.

ELKILauncher() - Constructor for class de.lmu.ifi.dbs.elki.application.ELKILauncher

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

Base LogRecord class used in ELKI.

ELKILogRecord(Level, CharSequence) - Constructor for class de.lmu.ifi.dbs.elki.logging.ELKILogRecord

Constructor.

ELKIServiceLoader - Class in de.lmu.ifi.dbs.elki.utilities

Class that emulates the behavior of an java ServiceLoader, except that the classes are not automatically instantiated.

ELKIServiceLoader() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceLoader

Constructor - do not use.

ELKIServiceRegistry - Class in de.lmu.ifi.dbs.elki.utilities

Registry of available implementations in ELKI.

ELKIServiceRegistry() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry

Do not use constructor.

ELKIServiceRegistry.Entry - Class in de.lmu.ifi.dbs.elki.utilities

Entry in the service registry.

ELKIServiceRegistry.Entry() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry.Entry

ELKIServiceScanner - Class in de.lmu.ifi.dbs.elki.utilities

A collection of inspection-related utility functions.

ELKIServiceScanner() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner

Static methods only.

ELKIServiceScanner.ClassSorter - Class in de.lmu.ifi.dbs.elki.utilities

Sort classes by their class name.

ELKIServiceScanner.ClassSorter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner.ClassSorter

ELKIServiceScanner.DirClassIterator - Class in de.lmu.ifi.dbs.elki.utilities

Class to iterate over a directory tree.

ELKIServiceScanner.DirClassIterator(File) - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner.DirClassIterator

Constructor from Directory

ellipsoidVincentyFormulaDeg(double, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil

Compute the approximate great-circle distance of two points.

ellipsoidVincentyFormulaRad(double, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil

Compute the approximate great-circle distance of two points.

ellipticalArc(double, double, double, double, double, double, double) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPath

Elliptical arc curve to the given coordinates.

ellipticalArc(double, double, double, double, double, double[]) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPath

Elliptical arc curve to the given coordinates.

ellipticalArc(Vector, double, double, double, Vector) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPath

Elliptical arc curve to the given coordinates.

EM<V extends NumberVector,M extends MeanModel> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.em

Clustering by expectation maximization (EM-Algorithm), also known as Gaussian Mixture Modeling (GMM).

EM(int, double, EMClusterModelFactory<V, M>, int, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.em.EM

Constructor.

em - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.EMOutlier.Parameterizer

EM clustering algorithm to run.

EM.Parameterizer<V extends NumberVector,M extends MeanModel> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.em

Parameterization class.

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

EM_DELTA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.P3C.Parameterizer

Threshold when to stop EM iterations.

embedOrThumbnail(int, PlotItem, VisualizationTask, Element) - Method in class de.lmu.ifi.dbs.elki.visualization.gui.overview.OverviewPlot

Produce thumbnail for a visualizer.

EMBLEM_IMPORTANT - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon

EMBORDER - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization.Instance

Generic tags to indicate the type of element.

emClustering - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.EMOutlier

Inner algorithm.

EMClusterModel<M extends MeanModel> - Interface in de.lmu.ifi.dbs.elki.algorithm.clustering.em

Models useable in EM clustering.

EMClusterModelFactory<V extends NumberVector,M extends MeanModel> - Interface in de.lmu.ifi.dbs.elki.algorithm.clustering.em

Factory for initializing the EM models.

EMClusterVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster

Visualizer for generating SVG-Elements containing ellipses for first, second and third standard deviation.

EMClusterVisualization() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization

Constructor

EMClusterVisualization.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster

Instance.

EMClusterVisualization.Instance(VisualizationTask, VisualizationPlot, double, double, Projection) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization.Instance

Constructor

emDelta - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.P3C

Threshold when to stop EM iterations.

emDelta - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.P3C.Parameterizer

Threshold when to stop EM iterations.

EMGOlivierNorbergEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator

Naive distribution estimation using mean and sample variance.

EMGOlivierNorbergEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.EMGOlivierNorbergEstimator

Private constructor, use static instance!

EMGOlivierNorbergEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator

Parameterization class.

EMGOlivierNorbergEstimator.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.EMGOlivierNorbergEstimator.Parameterizer

EMModel - Class in de.lmu.ifi.dbs.elki.data.model

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

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

Constructor.

EMOutlier<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.clustering

outlier detection algorithm using EM Clustering.

EMOutlier(EM<V, ?>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.EMOutlier

Constructor with an existing em clustering algorithm.

EMOutlier.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.clustering

Parameterization class.

EMOutlier.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.EMOutlier.Parameterizer

EMPTY - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.ArffParser

Empty line pattern.

EMPTY - Static variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.Rec

Empty list.

EMPTY_ALIASES - Static variable in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry.Entry

Reusable empty array.

EMPTY_CHILDREN - Static variable in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPNode

Constant for leaf nodes.

EMPTY_DISTS - Static variable in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDList

Empty.

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

Represents an empty enumeration.

EMPTY_IDS - Static variable in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDList

Empty.

EMPTY_INTS - Static variable in class de.lmu.ifi.dbs.elki.math.MathUtil

Empty integer array.

EMPTY_ITERATOR - Static variable in class de.lmu.ifi.dbs.elki.database.ids.EmptyDBIDs

Empty DBID iterator.

EMPTY_ITERATOR - Static variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy

Empty iterator.

EMPTY_LABELS - Static variable in class de.lmu.ifi.dbs.elki.data.LabelList

Empty label list.

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.

EMPTY_STRING - Static variable in class de.lmu.ifi.dbs.elki.utilities.FormatUtil

Preallocated exceptions.

EmptyDatabaseConnection - Class in de.lmu.ifi.dbs.elki.datasource

Pseudo database that is empty.

EmptyDatabaseConnection() - Constructor for class de.lmu.ifi.dbs.elki.datasource.EmptyDatabaseConnection

Constructor.

EMPTYDBIDS - Static variable in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil

Final, global copy of empty DBIDs.

EmptyDBIDs - Class in de.lmu.ifi.dbs.elki.database.ids

Empty DBID collection.

EmptyDBIDs() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.EmptyDBIDs

Constructor.

EmptyDBIDs.EmptyDBIDIterator - Class in de.lmu.ifi.dbs.elki.database.ids

Iterator for empty DBIDs-

EmptyDBIDs.EmptyDBIDIterator() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.EmptyDBIDs.EmptyDBIDIterator

emptyIterator() - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy

Get an empty hierarchy iterator.

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

A stack holding the empty page ids.

emptyPagesSize - Variable in class de.lmu.ifi.dbs.elki.index.tree.TreeIndexHeader

The number of bytes additionally needed for the listing of empty pages of the headed page file.

EmptyParameterization - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization

Parameterization handler that only allows the use of default values.

EmptyParameterization() - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.EmptyParameterization

enabled() - Method in interface de.lmu.ifi.dbs.elki.visualization.VisualizationMenuAction

Indicate if the menu option is enabled or greyed out.

enabled() - Method in interface de.lmu.ifi.dbs.elki.visualization.VisualizationMenuToggle

Indicate if the menu option is enabled or greyed out.

enabled() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.actions.ClusterStyleAction.SetStyleAction

enableExport(boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.gui.ResultWindow.DynamicMenu

Enable / disable the export menu.

enableOverview(boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.gui.ResultWindow.DynamicMenu

Enable / disable the overview menu.

enableStart() - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea

Enable capturing of 'mousedown' events.

enableStop() - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea

Enable capturing of 'mousemove' and 'mouseup' events.

ENABLEVIS_ID - Static variable in class de.lmu.ifi.dbs.elki.visualization.VisualizerParameterizer.Parameterizer

Parameter to enable visualizers Key: -vis.enable Default: ELKI core

enableVisualizers - Variable in class de.lmu.ifi.dbs.elki.visualization.VisualizerParameterizer.Parameterizer

Pattern to enable visualizers

encoder - Variable in class de.lmu.ifi.dbs.elki.utilities.io.ByteArrayUtil.StringSerializer

Encoder.

end - Variable in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs.Slice

Slice positions.

end - Variable in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs.Slice

Slice positions.

end - Variable in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDPair.Slice

Slice positions.

end() - Method in interface de.lmu.ifi.dbs.elki.logging.statistics.Duration

Finish the timer.

end - Variable in class de.lmu.ifi.dbs.elki.logging.statistics.MillisTimeDuration

Tracking variables.

end() - Method in class de.lmu.ifi.dbs.elki.logging.statistics.MillisTimeDuration

end - Variable in class de.lmu.ifi.dbs.elki.logging.statistics.NanoDuration

Tracking variables.

end() - Method in class de.lmu.ifi.dbs.elki.logging.statistics.NanoDuration

end - Variable in class de.lmu.ifi.dbs.elki.parallel.ParallelExecutor.BlockArrayRunner

End position

end - Variable in class de.lmu.ifi.dbs.elki.utilities.io.LineReader

Current position, and length of buffer

end - Variable in class de.lmu.ifi.dbs.elki.utilities.io.Tokenizer

Current positions of result and iterator.

endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in interface de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea.DragListener

Method called when a drag was ended.

endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea

Method called when a drag was ended.

endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance

endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotSelectionVisualization.Instance

endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolAxisRangeVisualization.Instance

endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolLineVisualization.Instance

endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.MoveObjectsToolVisualization.Instance

endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolCubeVisualization.Instance

endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolDotVisualization.Instance

endindex - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSXi.SteepArea

End index of down-area

endIndex - Variable in class de.lmu.ifi.dbs.elki.data.model.OPTICSModel

End index

enlargement(SpatialComparable, SpatialComparable) - Static method in class de.lmu.ifi.dbs.elki.data.spatial.SpatialUtil

Compute the enlargement obtained by adding an object to an existing object.

enlargementScaled(SpatialComparable, SpatialComparable, double) - Static method in class de.lmu.ifi.dbs.elki.data.spatial.SpatialUtil

Compute the enlargement obtained by adding an object to an existing object.

EnsembleEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality

Ensemble estimator taking the median of three of our best estimators.

EnsembleEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.EnsembleEstimator

EnsembleVoting - Interface in de.lmu.ifi.dbs.elki.utilities.ensemble

Interface for ensemble voting rules

EnsembleVotingInverseMultiplicative - Class in de.lmu.ifi.dbs.elki.utilities.ensemble

Inverse multiplicative voting: 1-product(1-s_i)

EnsembleVotingInverseMultiplicative() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingInverseMultiplicative

Constructor.

EnsembleVotingInverseMultiplicative.Parameterizer - Class in de.lmu.ifi.dbs.elki.utilities.ensemble

Parameterization class.

EnsembleVotingInverseMultiplicative.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingInverseMultiplicative.Parameterizer

EnsembleVotingMax - Class in de.lmu.ifi.dbs.elki.utilities.ensemble

Simple combination rule, by taking the maximum.

EnsembleVotingMax() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMax

Constructor.

EnsembleVotingMean - Class in de.lmu.ifi.dbs.elki.utilities.ensemble

Simple combination rule, by taking the mean

EnsembleVotingMean() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMean

Constructor.

EnsembleVotingMedian - Class in de.lmu.ifi.dbs.elki.utilities.ensemble

Simple combination rule, by taking the median.

EnsembleVotingMedian(double) - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMedian

Constructor.

EnsembleVotingMedian.Parameterizer - Class in de.lmu.ifi.dbs.elki.utilities.ensemble

Parameterization class.

EnsembleVotingMedian.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMedian.Parameterizer

EnsembleVotingMin - Class in de.lmu.ifi.dbs.elki.utilities.ensemble

Simple combination rule, by taking the minimum.

EnsembleVotingMin() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMin

Constructor.

EnsembleVotingMultiplicative - Class in de.lmu.ifi.dbs.elki.utilities.ensemble

Inverse multiplicative voting: product(s_i)

EnsembleVotingMultiplicative() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMultiplicative

Constructor.

EnsembleVotingMultiplicative.Parameterizer - Class in de.lmu.ifi.dbs.elki.utilities.ensemble

Parameterization class.

EnsembleVotingMultiplicative.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMultiplicative.Parameterizer

ensureArray(DBIDs) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil

Ensure that the given DBIDs are array-indexable.

ensureBuffer(int, ByteBuffer, WritableByteChannel) - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.BundleWriter

Ensure the buffer is large enough.

ensureClusteringResult(Database, Result) - Static method in class de.lmu.ifi.dbs.elki.result.ResultUtil

Ensure that the result contains at least one Clustering.

ensureCompleted(FiniteProgress) - Method in class de.lmu.ifi.dbs.elki.logging.Logging

Increment a progress (unless null).

ensureCompleted(Logging) - Method in class de.lmu.ifi.dbs.elki.logging.progress.FiniteProgress

Ensure that the progress was completed, to make progress bars disappear

ensureModifiable(DBIDs) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil

Ensure modifiable.

ensureSelectionResult(Database) - Static method in class de.lmu.ifi.dbs.elki.result.ResultUtil

Ensure that there also is a selection container object.

ensureSet(DBIDs) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil

Ensure that the given DBIDs support fast "contains" operations.

ensureSize() - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPNode

Ensure we have enough storage.

ensureSize(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs

Resize as desired.

ensureSize(int) - Method in class de.lmu.ifi.dbs.elki.persistent.OnDiskArray

Ensure that the file can fit the given number of records.

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

The entries (children) of this node.

entries - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.split.TopologicalSplitter.Split

The entries we process.

entropy - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.ClusterContingencyTable

Entropy-based measures

Entropy - Class in de.lmu.ifi.dbs.elki.evaluation.clustering

Entropy based measures.

Entropy(ClusterContingencyTable) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Constructor.

entropyConditionalFirst() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Get the conditional entropy of the first clustering.

entropyConditionalSecond() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Get the conditional entropy of the first clustering.

entropyFirst - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Entropy in first

entropyFirst() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Get the entropy of the first clustering using Log_2.

entropyJoint - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Joint entropy

entropyJoint() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Get the joint entropy of both clusterings (not normalized, 0 = equal)

entropyMutualInformation() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Get the mutual information (not normalized, 0 = equal)

entropyNMIJoint() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Get the joint-normalized mutual information (normalized, 0 = unequal)

entropyNMIMax() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Get the max-normalized mutual information (normalized, 0 = unequal)

entropyNMIMin() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Get the min-normalized mutual information (normalized, 0 = unequal)

entropyNMISqrt() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Get the sqrt-normalized mutual information (normalized, 0 = unequal)

entropyNMISum() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Get the sum-normalized mutual information (normalized, 0 = unequal)

entropyPowers() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Get Powers entropy (normalized, 0 = equal) Powers = 1 - NMI_Sum

entropySecond - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Entropy in second

entropySecond() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy

Get the entropy of the second clustering using Log_2.

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.IndexTreePath

The entry of this component.

entry - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.DistanceEntry

The entry of the Index.

entry - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.RStarTreeKNNQuery.DoubleDistanceEntry

Referenced entry

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

The first entry of this pair.

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

The second entry of this pair.

entrySet() - Method in class de.lmu.ifi.dbs.elki.visualization.gui.overview.RectangleArranger

The items contained in the map.

enumClass - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.EnumParameter

Reference to the actual enum type, for T.valueOf().

EnumParameter<E extends Enum<E>> - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters

Parameter class for a parameter specifying an enum type.

EnumParameter(OptionID, Class<E>, E) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.EnumParameter

Constructs an enum parameter with the given optionID, constraints and default value.

EnumParameter(OptionID, Class<E>, boolean) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.EnumParameter

Constructs an enum parameter with the given optionID, constraints and default value.

EnumParameter(OptionID, Class<E>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.EnumParameter

Constructs an enum parameter with the given optionID, constraints and default value.

EnumParameterConfigurator - Class in de.lmu.ifi.dbs.elki.gui.configurator

Panel to configure EnumParameters by offering a dropdown to choose from.

EnumParameterConfigurator(EnumParameter<?>, JComponent) - Constructor for class de.lmu.ifi.dbs.elki.gui.configurator.EnumParameterConfigurator

EpanechnikovKernelDensityFunction - Class in de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions

Epanechnikov kernel density estimator.

EpanechnikovKernelDensityFunction() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.EpanechnikovKernelDensityFunction

Private, empty constructor.

EpanechnikovKernelDensityFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions

Parameterization stub.

EpanechnikovKernelDensityFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.EpanechnikovKernelDensityFunction.Parameterizer

eps - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.OUTRES

The epsilon (in 2d) parameter

eps - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.OUTRES.Parameterizer

Query radius

EPS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenvalueDecomposition

Epsilon.

EPS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.SingularValueDecomposition

epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.COPAC.Settings

Epsilon value for GDBSCAN.

epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.FourC.Settings

Query radius epsilon.

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

Holds the epsilon radius threshold.

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

Holds the epsilon radius threshold.

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

Range to query with.

epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.AbstractRangeQueryNeighborPredicate.Parameterizer

Range to query with

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

Range to query with

epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.EpsilonNeighborPredicate.Instance

Range to query with

epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.EpsilonNeighborPredicate.Parameterizer

Range to query with

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

Holds the maximum distance to search for objects (performance parameter)

epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.AbstractOPTICS.Parameterizer

Epsilon radius.

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

Epsilon radius threshold.

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

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

Holds the value of DiSH.Parameterizer.EPSILON_ID.

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

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

Query radius parameter epsilon.

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

Holds the value of SUBCLU.EPSILON_ID.

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

epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.FDBSCAN.Parameterizer

Epsilon radius

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

Epsilon radius

epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.FDBSCANNeighborPredicate.Instance

The epsilon distance a neighbor may have at most.

epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.FDBSCANNeighborPredicate.Parameterizer

Epsilon radius

epsilon - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex

The epsilon value for each dimension.

epsilon - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex.Factory

The epsilon value for each dimension.

epsilon - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex.Factory.Parameterizer

The epsilon value for each dimension.

epsilon - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance

The current epsilon value.

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

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

EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.AbstractOPTICS.Parameterizer

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

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

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

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

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_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.HiSC.Parameterizer

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_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.SUBCLU

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

EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex.Factory

A comma separated list of positive doubles specifying the maximum radius of the neighborhood to be considered in each dimension for determination of the preference vector (default is DiSHPreferenceVectorIndex.Factory.DEFAULT_EPSILON in each dimension).

EpsilonNeighborPredicate<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan

The default DBSCAN and OPTICS neighbor predicate, using an epsilon-neighborhood.

EpsilonNeighborPredicate(double, DistanceFunction<? super O>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.EpsilonNeighborPredicate

Full constructor.

EpsilonNeighborPredicate.Instance - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan

Instance for a particular data set.

EpsilonNeighborPredicate.Instance(double, RangeQuery<?>, DBIDs) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.EpsilonNeighborPredicate.Instance

Constructor.

EpsilonNeighborPredicate.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan

Parameterization class

EpsilonNeighborPredicate.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.EpsilonNeighborPredicate.Parameterizer

epsilons - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.OUTRES.KernelDensityEstimator

Epsilon values for different subspace dimensionalities

epsilonsq - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.COPACNeighborPredicate

Squared value of epsilon.

epsilonsq - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.FDBSCANNeighborPredicate.Instance

The epsilon distance a neighbor may have at most.

equal(DBIDRef, DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory

Compare two DBIDs, for equality testing.

equal(DBIDRef, DBIDRef) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil

Test two DBIDs for equality.

equal(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory

equal(long[], long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil

Test two bitsets for equality

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.DeLiClu.SpatialObjectPair

equals is used in updating the heap!

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

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

equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.DenseItemset

equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.OneItemset

equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.SmallDenseItemset

equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.SparseItemset

equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary.Individuum

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 class de.lmu.ifi.dbs.elki.data.ExternalID

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

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(SpatialComparable, SpatialComparable) - Static method in class de.lmu.ifi.dbs.elki.data.spatial.SpatialUtil

Test two SpatialComparables for equality.

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

Indicates if the specified object is equal to this subspace, i.e. if the specified object is a Subspace and is built of the same dimensions than this subspace.

equals(Object) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBID

Deprecated.

equals(Object) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDRef

Deprecated.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.database.ids.EmptyDBIDs.EmptyDBIDIterator

equals(Object) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs.Itr

equals(Object) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBID

Deprecated.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBID.Itr

equals(Object) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDPair

equals(Object) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDRange.Itr

equals(Object) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDVar.Itr

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.adapter.AbstractSimilarityAdapter

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

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram.HistogramIntersectionDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram.HSBHistogramQuadraticDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram.RGBHistogramQuadraticDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.AbsolutePearsonCorrelationDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.AbsoluteUncenteredCorrelationDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.PearsonCorrelationDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.SquaredPearsonCorrelationDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.SquaredUncenteredCorrelationDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.UncenteredCorrelationDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.WeightedPearsonCorrelationDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.WeightedSquaredPearsonCorrelationDistanceFunction

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

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedDoubleDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedFloatDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.FileBasedDoubleDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.FileBasedFloatDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.geo.DimensionSelectingLatLngDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.geo.LatLngDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.geo.LngLatDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.histogram.HistogramMatchDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.histogram.KolmogorovSmirnovDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.EuclideanDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.LPNormDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.ManhattanDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.MaximumDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.MinimumDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.SquaredEuclideanDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedEuclideanDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedLPNormDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedManhattanDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedMaximumDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedSquaredEuclideanDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.ChiSquaredDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.JeffreyDivergenceDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.KullbackLeiblerDivergenceAsymmetricDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.KullbackLeiblerDivergenceReverseAsymmetricDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.SqrtJensenShannonDivergenceDistanceFunction

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

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.AbstractDimensionsSelectingDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.OnedimensionalDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.AbstractEditDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.EDRDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.ERPDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.LCSSDistanceFunction

equals(Object) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments.Segment

equals(Object) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.DistanceResultAdapter

Deprecated.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.FilteredDistanceResultAdapter

Deprecated.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.OutlierScoreAdapter

Deprecated.

equals(Object) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.SimpleAdapter

Deprecated.

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

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

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

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.IndexTreePath

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.query.DoubleDistanceSearchCandidate

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

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.math.linearalgebra.Matrix

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

equals(double[], double[]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath

Compare for equality.

equals(double[][], double[][]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath

Test for equality

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

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

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

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

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.DoubleObjPair

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.visualization.VisualizationTask

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

Returns a string representation of this equation system.

equationsToString(NumberFormat) - 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.statistics.distribution.NormalDistribution

Error function for Gaussian distributions = Normal distributions.

ERFAPP_A - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution

Coefficients for erf approximation.

ERFAPP_B - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution

Coefficients for erf approximation.

ERFAPP_C - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution

Coefficients for erf approximation.

ERFAPP_D - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution

Coefficients for erf approximation.

ERFAPP_P - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution

Coefficients for erf approximation.

ERFAPP_Q - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution

Coefficients for erf approximation.

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

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

erfinv(double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution

Inverse error function.

ERFINV_A - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution

Coefficients for erfinv approximation, rational version

ERFINV_B - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution

Coefficients for erfinv approximation, rational version

ERFINV_C - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution

Coefficients for erfinv approximation, rational version

ERFINV_D - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution

Coefficients for erfinv approximation, rational version

ERiC<V extends NumberVector> - 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(ERiC.Settings) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ERiC

Constructor.

ERiC.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation

Parameterization class.

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

ERiC.Settings - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation

Class to wrap the ERiC settings.

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

ERiC.Settings.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation

Parameterization class.

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

ERiCNeighborPredicate<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan

ERiC neighborhood predicate.

ERiCNeighborPredicate(ERiC.Settings) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.ERiCNeighborPredicate

Constructor.

ERiCNeighborPredicate.Instance - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan

Instance for a particular data set.

ERiCNeighborPredicate.Instance(DBIDs, DataStore<PCAFilteredResult>, Relation<? extends NumberVector>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.ERiCNeighborPredicate.Instance

Constructor.

ERiCNeighborPredicate.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan

Parameterization class.

ERiCNeighborPredicate.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.ERiCNeighborPredicate.Parameterizer

ERPDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries

Edit Distance With Real Penalty distance for numerical vectors.

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

Constructor.

ERPDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries

Parameterization class.

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

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

Output stream for error output.

ERR_DIMENSIONS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector

Error message (in assertions!)

ERR_DIMENSIONS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath

Error message (in assertions!)

ERR_MATRIX_DIMENSIONS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix

Error when matrix dimensions do not agree.

ERR_MATRIX_DIMENSIONS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath

Error message (in assertions!)

ERR_MATRIX_INNERDIM - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix

Error when matrix inner dimensions do not agree.

ERR_MATRIX_INNERDIM - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector

Error message (in assertions!)

ERR_MATRIX_INNERDIM - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath

Error message (in assertions!)

ERR_NOTRECTANGULAR - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix

Error: matrix not rectangular.

ERR_REINDEX - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix

Error: matrix indexes incorrect

ERR_TOO_LITTLE_WEIGHT - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.CovarianceMatrix

Error message reported when too little data (weight <= 1) in matrix.

ERR_VEC_DIMENSIONS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector

Error message (in assertions!)

ERR_VEC_DIMENSIONS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath

Error message (in assertions!)

errformat - Variable in class de.lmu.ifi.dbs.elki.gui.util.LogPane

Formatter for error messages

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

Formatter for error messages

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

Log a message at the 'severe' level.

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

Log a message at the 'severe' level.

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

Format a log record for error output, including a stack trace if available.

ErrorFormatter() - Constructor for class de.lmu.ifi.dbs.elki.logging.ErrorFormatter

Constructor.

errors - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.AbstractParameterization

Errors

errors - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.UnParameterization

Errors

errorsTo(Parameterization) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ChainedParameterization

Set the error target, since there is no unique way where errors can be reported.

errorTarget - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ChainedParameterization

Error target

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

Returns the error vectors after projection.

errStyle - Variable in class de.lmu.ifi.dbs.elki.gui.util.LogPane

Error message style

esq - Variable in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel

Derived model parameters: e and e squared.

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractExpMADEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLMMEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMADEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMeanVarianceEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMOMEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMADEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMeanVarianceEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMOMEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.DistributionEstimator

General form of the parameter estimation

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GammaChoiWetteEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LaplaceMLEEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogGammaChoiWetteEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogNormalLevenbergMarquardtKDEEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta.BestFitEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta.TrimmedEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta.WinsorisingEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.NormalLevenbergMarquardtKDEEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.RayleighMLEEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.UniformEnhancedMinMaxEstimator

estimate(double, double, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.UniformEnhancedMinMaxEstimator

Estimate from simple characteristics.

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.UniformMinMaxEstimator

estimate(DoubleMinMax) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.UniformMinMaxEstimator

Estimate parameters from minimum and maximum observed.

estimate(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.UniformMinMaxEstimator

Estimate parameters from minimum and maximum observed.

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.WaldMLEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.WeibullLogMOMEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.AbstractIntrinsicDimensionalityEstimator

estimate(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.AbstractIntrinsicDimensionalityEstimator

estimate(double[], int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.AbstractIntrinsicDimensionalityEstimator

estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.AggregatedHillEstimator

estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.EnsembleEstimator

estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.GEDEstimator

estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.HillEstimator

estimate(A, NumberArrayAdapter<?, A>) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.IntrinsicDimensionalityEstimator

Estimate from a distance list.

estimate(A, NumberArrayAdapter<?, A>, int) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.IntrinsicDimensionalityEstimator

Estimate from a distance list.

estimate(double[]) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.IntrinsicDimensionalityEstimator

Estimate from a distance list.

estimate(double[], int) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.IntrinsicDimensionalityEstimator

Estimate from a distance list.

estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.LMomentsEstimator

estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.MOMEstimator

estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.PWM2Estimator

estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.PWMEstimator

estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.RVEstimator

estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.ZipfEstimator

estimateDensities(Relation<O>, KNNQuery<O>, DBIDs, WritableDataStore<double[]>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.KDEOS

Perform the kernel density estimation step.

estimateDensity(NumberVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.DiagonalGaussianModel

estimateDensity(NumberVector) - Method in interface de.lmu.ifi.dbs.elki.algorithm.clustering.em.EMClusterModel

Estimate the likelihood of a vector.

estimateDensity(NumberVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.MultivariateGaussianModel

estimateDensity(NumberVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.SphericalGaussianModel

estimateEigenvalue(double[][], double[]) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.FastMultidimensionalScalingTransform

Estimate the (singed!)

estimateFromExpMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractExpMADEstimator

estimateFromExpMedianMAD(double, double) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExpMADDistributionEstimator

General form of the parameter estimation

estimateFromExpMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogGammaAlternateExpMADEstimator

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLMMEstimator

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialLMMEstimator

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GammaLMMEstimator

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedExtremeValueLMMEstimator

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedLogisticAlternateLMMEstimator

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedParetoLMMEstimator

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GumbelLMMEstimator

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LaplaceLMMEstimator

estimateFromLMoments(double[]) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LMMDistributionEstimator

Estimate from the L-Moments.

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogisticLMMEstimator

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogNormalBilkovaLMMEstimator

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogNormalLMMEstimator

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.NormalLMMEstimator

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.RayleighLMMEstimator

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.SkewGNormalLMMEstimator

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.UniformLMMEstimator

estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.WeibullLMMEstimator

estimateFromLogMeanVariance(MeanVariance, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMeanVarianceEstimator

Estimate the distribution from mean and variance.

estimateFromLogMeanVariance(MeanVariance, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogGammaLogMOMEstimator

estimateFromLogMeanVariance(MeanVariance, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogNormalLogMOMEstimator

estimateFromLogMedianMAD(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMADEstimator

estimateFromLogMedianMAD(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogGammaLogMADEstimator

estimateFromLogMedianMAD(double, double, double) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogMADDistributionEstimator

General form of the parameter estimation

estimateFromLogMedianMAD(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogNormalLogMADEstimator

estimateFromLogMedianMAD(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.WeibullLogMADEstimator

estimateFromLogStatisticalMoments(StatisticalMoments, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMeanVarianceEstimator

estimateFromLogStatisticalMoments(StatisticalMoments, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMOMEstimator

estimateFromLogStatisticalMoments(StatisticalMoments, double) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogMOMDistributionEstimator

General form of the parameter estimation

estimateFromMeanVariance(MeanVariance) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMeanVarianceEstimator

estimateFromMeanVariance(MeanVariance) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMOMEstimator

estimateFromMeanVariance(MeanVariance) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GammaMOMEstimator

estimateFromMeanVariance(MeanVariance) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.MeanVarianceDistributionEstimator

Estimate the distribution from mean and variance.

estimateFromMeanVariance(MeanVariance) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.NormalMOMEstimator

estimateFromMeanVariance(MeanVariance) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.WaldMOMEstimator

estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMADEstimator

estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.CauchyMADEstimator

estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMADEstimator

estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMedianEstimator

estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GammaMADEstimator

estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GumbelMADEstimator

estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LaplaceMADEstimator

estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogisticMADEstimator

estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogLogisticMADEstimator

estimateFromMedianMAD(double, double) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.MADDistributionEstimator

General form of the parameter estimation

estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.NormalMADEstimator

estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.RayleighMADEstimator

estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.UniformMADEstimator

estimateFromStatisticalMoments(StatisticalMoments) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMeanVarianceEstimator

estimateFromStatisticalMoments(StatisticalMoments) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMOMEstimator

estimateFromStatisticalMoments(StatisticalMoments) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.EMGOlivierNorbergEstimator

estimateFromStatisticalMoments(StatisticalMoments) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.MOMDistributionEstimator

General form of the parameter estimation

EstimateIntrinsicDimensionality<O> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics

Estimate global average intrinsic dimensionality of a data set.

EstimateIntrinsicDimensionality(DistanceFunction<? super O>, IntrinsicDimensionalityEstimator, double, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.EstimateIntrinsicDimensionality

Constructor.

EstimateIntrinsicDimensionality.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics

Parameterization class.

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

estimateViewport() - Method in class de.lmu.ifi.dbs.elki.visualization.projections.AffineProjection

estimateViewport() - Method in interface de.lmu.ifi.dbs.elki.visualization.projections.Projection2D

Estimate the viewport requirements

estimateViewport() - Method in class de.lmu.ifi.dbs.elki.visualization.projections.Simple2D

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

Perform an estimation of y on the specified matrix.

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

Performs an estimation of y on the specified x value.

estimator - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.IDOS

Estimator for intrinsic dimensionality.

estimator - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.IDOS.Parameterizer

Estimator for intrinsic dimensionality.

estimator - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.IntrinsicDimensionalityOutlier

Estimator for intrinsic dimensionality.

estimator - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.IntrinsicDimensionalityOutlier.Parameterizer

Estimator for intrinsic dimensionality.

estimator - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.EstimateIntrinsicDimensionality

Estimation method.

estimator - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.EstimateIntrinsicDimensionality.Parameterizer

Estimation method.

ESTIMATOR_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.IDOS.Parameterizer

The class used for estimating the intrinsic dimensionality.

ESTIMATOR_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.IntrinsicDimensionalityOutlier.Parameterizer

Class to use for estimating the ID.

ESTIMATOR_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.EstimateIntrinsicDimensionality.Parameterizer

Estimation method

estimators - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseBetaNormalization

Stores the distribution estimators

estimators - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseBetaNormalization.Parameterizer

Stores the distribution estimators

estimators - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseCDFNormalization

Stores the distribution estimators

estimators - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseCDFNormalization.Parameterizer

Stores the distribution estimators

etag - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotSelectionVisualization.Instance

Element for the events

etag - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolAxisRangeVisualization.Instance

Element for the rectangle to add listeners

etag - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolLineVisualization.Instance

Element for the rectangle to add listeners

etag - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.MoveObjectsToolVisualization.Instance

Element for the rectangle to add listeners

etag - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolCubeVisualization.Instance

Element for the rectangle to add listeners.

etag - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolDotVisualization.Instance

Element for the rectangle to add listeners

EUCLIDEAN_KAPPA - Static variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGHyperSphere

Factor used for approximating circles with cubic beziers.

EuclideanDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski

Euclidean distance for NumberVectors.

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

Deprecated.

Use static instance!

EuclideanDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski

Parameterization class.

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

EuclideanHashFunctionFamily - Class in de.lmu.ifi.dbs.elki.index.lsh.hashfamilies

2-stable hash function family for Euclidean distances.

EuclideanHashFunctionFamily(RandomFactory, double, int) - Constructor for class de.lmu.ifi.dbs.elki.index.lsh.hashfamilies.EuclideanHashFunctionFamily

Constructor.

EuclideanHashFunctionFamily.Parameterizer - Class in de.lmu.ifi.dbs.elki.index.lsh.hashfamilies

Parameterization class.

EuclideanHashFunctionFamily.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.lsh.hashfamilies.EuclideanHashFunctionFamily.Parameterizer

euclideanLength() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector

Returns the length of this vector.

euclideanLength(double[]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath

Euclidean length of the vector

EuclideanRStarTreeKNNQuery<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query

Instance of a KNN query for a particular spatial index.

EuclideanRStarTreeKNNQuery(AbstractRStarTree<?, ?, ?>, Relation<? extends O>) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.EuclideanRStarTreeKNNQuery

Constructor.

EuclideanRStarTreeRangeQuery<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query

Instance of a range query for a particular spatial index.

EuclideanRStarTreeRangeQuery(AbstractRStarTree<?, ?, ?>, Relation<? extends O>) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.EuclideanRStarTreeRangeQuery

Constructor.

EULERS_CONST - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GammaDistribution

Euler–Mascheroni constant

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

evals - Variable in class de.lmu.ifi.dbs.elki.gui.multistep.panels.EvaluationTabPanel

The data input configured

evals - Variable in class de.lmu.ifi.dbs.elki.gui.multistep.panels.OutputTabPanel

Algorithm step to run on.

evalTab - Variable in class de.lmu.ifi.dbs.elki.gui.multistep.MultiStepGUI

Evaluation panel.

evaluate(Cluster<?>, DoubleDBIDList) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.AbstractScoreEvaluation

evaluate(DBIDs, DoubleDBIDList) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.AbstractScoreEvaluation

evaluate(DBIDs, OutlierResult) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.AbstractScoreEvaluation

evaluate(ScoreEvaluation.Predicate<? super I>, I) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.AveragePrecisionEvaluation

evaluate(ScoreEvaluation.Predicate<? super I>, I) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.MaximumF1Evaluation

evaluate(ScoreEvaluation.Predicate<? super I>, I) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.PrecisionAtKEvaluation

evaluate(ScoreEvaluation.Predicate<? super I>, I) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.ROCEvaluation

evaluate(ScoreEvaluation.Predicate<? super I>, I) - Method in interface de.lmu.ifi.dbs.elki.evaluation.scores.ScoreEvaluation

Evaluate a given predicate and iterator.

evaluate(Cluster<?>, DoubleDBIDList) - Method in interface de.lmu.ifi.dbs.elki.evaluation.scores.ScoreEvaluation

Evaluate given a cluster (of positive elements) and a scoring list.

evaluate(DBIDs, DoubleDBIDList) - Method in interface de.lmu.ifi.dbs.elki.evaluation.scores.ScoreEvaluation

Evaluate given a list of positives and a scoring.

evaluate(DBIDs, OutlierResult) - Method in interface de.lmu.ifi.dbs.elki.evaluation.scores.ScoreEvaluation

Evaluate given a set of positives and a scoring.

EvaluateCIndex<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Compute the C-index of a data set.

EvaluateCIndex(DistanceFunction<? super O>, NoiseHandling) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateCIndex

Constructor.

EvaluateCIndex.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Parameterization class.

EvaluateCIndex.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateCIndex.Parameterizer

EvaluateClustering - Class in de.lmu.ifi.dbs.elki.evaluation.clustering

Evaluate a clustering result by comparing it to an existing cluster label.

EvaluateClustering(ClusteringAlgorithm<?>, boolean, boolean) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.EvaluateClustering

Constructor.

evaluateClustering(Database, Relation<? extends O>, DistanceQuery<O>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateCIndex

Evaluate a single clustering.

evaluateClustering(Database, Relation<? extends NumberVector>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs

Evaluate a single clustering.

evaluateClustering(Database, Relation<? extends NumberVector>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateDaviesBouldin

Evaluate a single clustering.

evaluateClustering(Database, Relation<? extends NumberVector>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluatePBMIndex

Evaluate a single clustering.

evaluateClustering(Database, Relation<O>, DistanceQuery<O>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSilhouette

Evaluate a single clustering.

evaluateClustering(Database, Relation<? extends NumberVector>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSimplifiedSilhouette

Evaluate a single clustering.

evaluateClustering(Database, Relation<? extends NumberVector>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSquaredErrors

Evaluate a single clustering.

evaluateClustering(Database, Relation<? extends NumberVector>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateVarianceRatioCriteria

Evaluate a single clustering.

EvaluateClustering.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.clustering

Parameterization class.

EvaluateClustering.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.EvaluateClustering.Parameterizer

EvaluateClustering.ScoreResult - Class in de.lmu.ifi.dbs.elki.evaluation.clustering

Result object for outlier score judgements.

EvaluateClustering.ScoreResult(ClusterContingencyTable) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.EvaluateClustering.ScoreResult

Constructor.

evaluateClusters(ArrayList<PROCLUS<V>.PROCLUSCluster>, long[][], Relation<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS

Evaluates the quality of the clusters.

EvaluateConcordantPairs<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Compute the Gamma Criterion of a data set.

EvaluateConcordantPairs(PrimitiveDistanceFunction<? super NumberVector>, NoiseHandling) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs

Constructor.

EvaluateConcordantPairs.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Parameterization class.

EvaluateConcordantPairs.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs.Parameterizer

EvaluateDaviesBouldin - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Compute the Davies-Bouldin index of a data set.

EvaluateDaviesBouldin(NumberVectorDistanceFunction<?>, NoiseHandling) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateDaviesBouldin

Constructor.

EvaluateDaviesBouldin.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Parameterization class.

EvaluateDaviesBouldin.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateDaviesBouldin.Parameterizer

EvaluateIntrinsicDimensionalityEstimators - Class in de.lmu.ifi.dbs.elki.application.experiments

Class for testing the estimation quality of intrinsic dimensionality estimators.

EvaluateIntrinsicDimensionalityEstimators(int, int, int, int, EvaluateIntrinsicDimensionalityEstimators.Aggregate, EvaluateIntrinsicDimensionalityEstimators.OutputFormat, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators

Constructor.

EvaluateIntrinsicDimensionalityEstimators.Aggregate - Enum in de.lmu.ifi.dbs.elki.application.experiments

Aggregation methods.

EvaluateIntrinsicDimensionalityEstimators.Aggregate() - Constructor for enum de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Aggregate

EvaluateIntrinsicDimensionalityEstimators.OutputFormat - Enum in de.lmu.ifi.dbs.elki.application.experiments

Output format

EvaluateIntrinsicDimensionalityEstimators.OutputFormat() - Constructor for enum de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.OutputFormat

EvaluateIntrinsicDimensionalityEstimators.Parameterizer - Class in de.lmu.ifi.dbs.elki.application.experiments

Parameterization class.

EvaluateIntrinsicDimensionalityEstimators.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Parameterizer

evaluateKNN(double[], ModifiableDoubleDBIDList, Relation<?>, TObjectIntHashMap<Object>, Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRetrievalPerformance.KNNEvaluator

Evaluate by simulating kNN classification for k=1...maxk

evaluateOrderingResult(int, SetDBIDs, DBIDs) - Method in class de.lmu.ifi.dbs.elki.evaluation.outlier.OutlierRankingEvaluation

evaluateOutlierResult(Database, OutlierResult) - Method in class de.lmu.ifi.dbs.elki.evaluation.histogram.ComputeOutlierHistogram

Evaluate a single outlier result as histogram.

evaluateOutlierResult(int, SetDBIDs, OutlierResult) - Method in class de.lmu.ifi.dbs.elki.evaluation.outlier.OutlierRankingEvaluation

EvaluatePBMIndex - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Compute the PBM of a data set Reference: M.

EvaluatePBMIndex(NumberVectorDistanceFunction<?>, NoiseHandling) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluatePBMIndex

Constructor.

EvaluatePBMIndex.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Parameterization class.

EvaluatePBMIndex.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluatePBMIndex.Parameterizer

EvaluatePrecomputedOutlierScores - Class in de.lmu.ifi.dbs.elki.application.greedyensemble

Class to load an outlier detection summary file, as produced by ComputeKNNOutlierScores, and compute popular evaluation metrics for it.

EvaluatePrecomputedOutlierScores(InputStep, Pattern, File, String) - Constructor for class de.lmu.ifi.dbs.elki.application.greedyensemble.EvaluatePrecomputedOutlierScores

Constructor.

EvaluatePrecomputedOutlierScores.Parameterizer - Class in de.lmu.ifi.dbs.elki.application.greedyensemble

Parameterization class.

EvaluatePrecomputedOutlierScores.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.application.greedyensemble.EvaluatePrecomputedOutlierScores.Parameterizer

EvaluateRankingQuality<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics

Evaluate a distance function with respect to kNN queries.

EvaluateRankingQuality(DistanceFunction<? super V>, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRankingQuality

Constructor.

EvaluateRankingQuality.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics

Parameterization class.

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

EvaluateRetrievalPerformance<O> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics

Evaluate a distance functions performance by computing the mean average precision, ROC, and NN classification performance when ranking the objects by distance.

EvaluateRetrievalPerformance(DistanceFunction<? super O>, double, RandomFactory, boolean, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRetrievalPerformance

Constructor.

EvaluateRetrievalPerformance.KNNEvaluator - Class in de.lmu.ifi.dbs.elki.algorithm.statistics

Evaluate kNN retrieval performance.

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

EvaluateRetrievalPerformance.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics

Parameterization class.

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

EvaluateRetrievalPerformance.RetrievalPerformanceResult - Class in de.lmu.ifi.dbs.elki.algorithm.statistics

Result object for MAP scores.

EvaluateRetrievalPerformance.RetrievalPerformanceResult(int, double, double, double[]) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRetrievalPerformance.RetrievalPerformanceResult

Constructor.

EvaluateSilhouette<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Compute the silhouette of a data set.

EvaluateSilhouette(DistanceFunction<? super O>, NoiseHandling, boolean) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSilhouette

Constructor.

EvaluateSilhouette(DistanceFunction<? super O>, boolean) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSilhouette

Constructor.

EvaluateSilhouette.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Parameterization class.

EvaluateSilhouette.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSilhouette.Parameterizer

EvaluateSimplifiedSilhouette - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Compute the simplified silhouette of a data set.

EvaluateSimplifiedSilhouette(NumberVectorDistanceFunction<?>, NoiseHandling, boolean) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSimplifiedSilhouette

Constructor.

EvaluateSimplifiedSilhouette.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Parameterization class.

EvaluateSimplifiedSilhouette.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSimplifiedSilhouette.Parameterizer

EvaluateSquaredErrors - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Evaluate a clustering by reporting the squared errors (SSE, SSQ), as used by k-means.

EvaluateSquaredErrors(NumberVectorDistanceFunction<?>, NoiseHandling) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSquaredErrors

Constructor.

EvaluateSquaredErrors.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Parameterization class.

EvaluateSquaredErrors.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSquaredErrors.Parameterizer

EvaluateVarianceRatioCriteria<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Compute the Variance Ratio Criteria of a data set.

EvaluateVarianceRatioCriteria(NoiseHandling, boolean) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateVarianceRatioCriteria

Constructor.

EvaluateVarianceRatioCriteria.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Parameterization class.

EvaluateVarianceRatioCriteria.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateVarianceRatioCriteria.Parameterizer

evaluationName - Variable in class de.lmu.ifi.dbs.elki.evaluation.classification.ConfusionMatrixEvaluationResult

Holds the used EvaluationProcedure.

EvaluationResult - Class in de.lmu.ifi.dbs.elki.result

Abstract evaluation result.

EvaluationResult(String, String) - Constructor for class de.lmu.ifi.dbs.elki.result.EvaluationResult

Constructor.

EvaluationResult.Measurement - Class in de.lmu.ifi.dbs.elki.result

Class representing a single measurement.

EvaluationResult.Measurement(String, double, double, double, boolean) - Constructor for class de.lmu.ifi.dbs.elki.result.EvaluationResult.Measurement

Constructor.

EvaluationResult.Measurement(String, double, double, double, double, boolean) - Constructor for class de.lmu.ifi.dbs.elki.result.EvaluationResult.Measurement

Constructor.

EvaluationResult.MeasurementGroup - Class in de.lmu.ifi.dbs.elki.result

A group of evaluation measurements.

EvaluationResult.MeasurementGroup(String) - Constructor for class de.lmu.ifi.dbs.elki.result.EvaluationResult.MeasurementGroup

Constructor.

evaluationStep - Variable in class de.lmu.ifi.dbs.elki.KDDTask

The evaluation step.

evaluationStep - Variable in class de.lmu.ifi.dbs.elki.KDDTask.Parameterizer

EvaluationStep - Class in de.lmu.ifi.dbs.elki.workflow

The "evaluation" step, where data is analyzed.

EvaluationStep(List<Evaluator>) - Constructor for class de.lmu.ifi.dbs.elki.workflow.EvaluationStep

Constructor.

EvaluationStep.Evaluation - Class in de.lmu.ifi.dbs.elki.workflow

Class to handle running the evaluators on a database instance.

EvaluationStep.Evaluation(ResultHierarchy, List<Evaluator>) - Constructor for class de.lmu.ifi.dbs.elki.workflow.EvaluationStep.Evaluation

Constructor.

EvaluationStep.Parameterizer - Class in de.lmu.ifi.dbs.elki.workflow

Parameterization class.

EvaluationStep.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.workflow.EvaluationStep.Parameterizer

EvaluationTabPanel - Class in de.lmu.ifi.dbs.elki.gui.multistep.panels

Panel to handle result evaluation

EvaluationTabPanel(InputTabPanel, AlgorithmTabPanel) - Constructor for class de.lmu.ifi.dbs.elki.gui.multistep.panels.EvaluationTabPanel

Constructor.

EvaluationVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj

Pseudo-Visualizer, that lists the cluster evaluation results found.

EvaluationVisualization() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.EvaluationVisualization

Constructor.

Evaluator - Interface in de.lmu.ifi.dbs.elki.evaluation

Interface for post-algorithm evaluations, such as histograms, outlier score evaluations, ...

EVALUATOR_ID - Static variable in class de.lmu.ifi.dbs.elki.workflow.EvaluationStep.Parameterizer

Parameter ID to specify the evaluators to run.

evaluators - Variable in class de.lmu.ifi.dbs.elki.workflow.EvaluationStep.Evaluation

Evaluators to run.

evaluators - Variable in class de.lmu.ifi.dbs.elki.workflow.EvaluationStep

Evaluators to run.

evaluators - Variable in class de.lmu.ifi.dbs.elki.workflow.EvaluationStep.Parameterizer

Evaluators to run

evaluteResult(Database, Clustering<?>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.EvaluateClustering

Evaluate a clustering result.

eventarea - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance

Sensitive (clickable) area

eventManager - Variable in class de.lmu.ifi.dbs.elki.database.AbstractDatabase

The event manager, collects events and fires them on demand.

EVT_DBLCLICK_DELAY - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.CircleSegmentsVisualizer.Instance.SegmentListenerProxy

Mouse double click time window in milliseconds TODO: does Batik have double click events?

exact - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceStatisticsWithClasses

Compute exactly (slower).

exact - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceStatisticsWithClasses.Parameterizer

Exactness flag.

EXACT_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceStatisticsWithClasses.Parameterizer

Flag to compute exact value range for binning.

exactMinMax(Relation<O>, DistanceQuery<O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceStatisticsWithClasses

Compute the exact maximum and minimum.

exception(CharSequence, 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.exceptions

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

excessOfMass() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.TempCluster

Excess of mass measure.

excludeNotCovered(ModifiableDoubleDBIDList, double, ModifiableDoubleDBIDList) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree

Retain all elements within the current cover.

execute() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.ParameterTabPanel

Execute the task.

executed - Variable in class de.lmu.ifi.dbs.elki.gui.multistep.panels.InputTabPanel

Signal when an database input has been executed.

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

Callback function that needs to be overridden with actual implementations.

executeStep() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.AlgorithmTabPanel

executeStep() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.EvaluationTabPanel

executeStep() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.InputTabPanel

executeStep() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.LoggingTabPanel

executeStep() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.OutputTabPanel

executeStep() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.ParameterTabPanel

Execute the configured step.

Executor - Interface in de.lmu.ifi.dbs.elki.parallel

Processor executor.

executor - Variable in class de.lmu.ifi.dbs.elki.parallel.ParallelCore

Executor service.

existed - Variable in class de.lmu.ifi.dbs.elki.persistent.OnDiskArrayPageFile

Whether or not the file originally existed

existed - Variable in class de.lmu.ifi.dbs.elki.persistent.PersistentPageFile

Whether we are initializing from an existing file.

existing - Variable in class de.lmu.ifi.dbs.elki.data.ClassLabel.Factory

Set for reusing the same objects.

existing - Variable in class de.lmu.ifi.dbs.elki.database.relation.ConvertToStringView

The database we use

exp - Variable in class de.lmu.ifi.dbs.elki.result.EvaluationResult.Measurement

Observed value, minimum, maximum, expected value.

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

DBSCAN-function expandCluster.

expandCluster(DBIDRef, int, WritableIntegerDataStore, T, ArrayModifiableDBIDs, FiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Instance

Set-based expand cluster implementation.

expandCluster(int, WritableIntegerDataStore, KNNQuery<O>, DBIDs, double, FiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.LSDBC

Set-based expand cluster implementation.

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

DBSCAN-function expandCluster adapted to SNN criterion.

expandClusterOrder(DBID, ClusterOrder, DistanceQuery<V>, FiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.FastOPTICS

OPTICS algorithm for processing a point, but with different density estimates

expandClusterOrder(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSHeap.Instance

OPTICS-function expandClusterOrder.

expandClusterOrder(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSList.Instance

OPTICS-function expandClusterOrder.

expandDBID(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.HiCO.Instance

expandDBID(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.GeneralizedOPTICS.Instance

Add the current DBID to the cluster order, and expand its neighbors if minPts and similar conditions are satisfied.

expandDBID(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.Instance

expandDBID(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.HiSC.Instance

expandDirNodes(SpatialPrimitiveDistanceFunction<NV>, DeLiCluNode, DeLiCluNode) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.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(SpatialPrimitiveDistanceFunction<NV>, DeLiCluNode, DeLiCluNode, DataStore<KNNList>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.DeLiClu

Expands the specified leaf nodes.

expandNode(O, KNNHeap, ComparableMinHeap<DoubleDistanceSearchCandidate>, double, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.EuclideanRStarTreeKNNQuery

expandNode(O, KNNHeap, ComparableMinHeap<DoubleDistanceSearchCandidate>, double, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.RStarTreeKNNQuery

expandNodes(DeLiCluTree, SpatialPrimitiveDistanceFunction<NV>, DeLiClu<NV>.SpatialObjectPair, DataStore<KNNList>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.DeLiClu

Expands the spatial nodes of the specified pair.

expansion - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree

Constant expansion rate. 2 would be the intuitive value, but the original version used 1.3, so we copy this.

expansion - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree.Factory

Constant expansion rate. 2 would be the intuitive value, but the original version used 1.3, so we copy this.

expansion - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree.Factory.Parameterizer

Expansion rate.

EXPANSION_ID - Static variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree.Factory.Parameterizer

Expansion rate of the tree (going upward).

expect - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.COP

Expected amount of outliers.

expect - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.COP.Parameterizer

Expected amount of outliers.

expect - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.trivial.TrivialGeneratedOutlier

Expected share of outliers.

expect - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.trivial.TrivialGeneratedOutlier.Parameterizer

Expected share of outliers

EXPECT_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.COP.Parameterizer

Expected share of outliers.

EXPECT_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.trivial.TrivialGeneratedOutlier.Parameterizer

Expected share of outliers

expected(int, int) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.AveragePrecisionEvaluation

expected(int, int) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.MaximumF1Evaluation

expected(int, int) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.PrecisionAtKEvaluation

expected(int, int) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.ROCEvaluation

expected(int, int) - Method in interface de.lmu.ifi.dbs.elki.evaluation.scores.ScoreEvaluation

Expected score for a random result.

expirePage(P) - Method in class de.lmu.ifi.dbs.elki.persistent.LRUCache

Write page through to disk.

explain - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredAutotuningRunner.Cand

Score

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

The amount of Variance explained by strong Eigenvalues

ExpMADDistributionEstimator<D extends Distribution> - Interface in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator

Distribuition estimators that use the method of moments (MOM) in exponentiated data.

EXPONENT_OVERFLOW - Static variable in class de.lmu.ifi.dbs.elki.utilities.FormatUtil

Preallocated exceptions.

ExponentialDistribution - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution

Exponential distribution.

ExponentialDistribution(double) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution

Constructor.

ExponentialDistribution(double, double) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution

Constructor.

ExponentialDistribution(double, Random) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution

Constructor.

ExponentialDistribution(double, double, Random) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution

Constructor.

ExponentialDistribution(double, double, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution

Constructor.

ExponentialDistribution.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution

Parameterization class

ExponentialDistribution.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution.Parameterizer

ExponentialLMMEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator

Estimate the parameters of a Gamma Distribution, using the methods of L-Moments (LMM).

ExponentialLMMEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialLMMEstimator

Constructor.

ExponentialLMMEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator

Parameterization class.

ExponentialLMMEstimator.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialLMMEstimator.Parameterizer

ExponentiallyModifiedGaussianDistribution - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution

Exponentially modified Gaussian (EMG) distribution (ExGaussian distribution) is a combination of a normal distribution and an exponential distribution.

ExponentiallyModifiedGaussianDistribution(double, double, double, Random) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentiallyModifiedGaussianDistribution

Constructor for ExGaussian distribution

ExponentiallyModifiedGaussianDistribution(double, double, double, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentiallyModifiedGaussianDistribution

Constructor for ExGaussian distribution

ExponentiallyModifiedGaussianDistribution(double, double, double) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentiallyModifiedGaussianDistribution

Constructor for ExGaussian distribution

ExponentiallyModifiedGaussianDistribution.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution

Parameterization class

ExponentiallyModifiedGaussianDistribution.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentiallyModifiedGaussianDistribution.Parameterizer

ExponentialMADEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator

Estimate Exponential distribution parameters using Median and MAD.

ExponentialMADEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMADEstimator

Private constructor, use static instance!

ExponentialMADEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator

Parameterization class.

ExponentialMADEstimator.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMADEstimator.Parameterizer

ExponentialMedianEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator

Estimate Exponential distribution parameters using Median and MAD.

ExponentialMedianEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMedianEstimator

Private constructor, use static instance!

ExponentialMedianEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator

Parameterization class.

ExponentialMedianEstimator.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMedianEstimator.Parameterizer

ExponentialMOMEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator

Estimate Exponential distribution parameters using the mean, which is the maximum-likelihood estimate (MLE), but not very robust.

ExponentialMOMEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMOMEstimator

Private constructor, use static instance!

ExponentialMOMEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator

Parameterization class.

ExponentialMOMEstimator.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMOMEstimator.Parameterizer

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

exportItem - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.ResultWindow.DynamicMenu

The "Export" button, to save the image

ExportVisualizations - Class in de.lmu.ifi.dbs.elki.visualization

Class that automatically generates all visualizations and exports them into SVG files.

ExportVisualizations(File, VisualizerParameterizer, double) - Constructor for class de.lmu.ifi.dbs.elki.visualization.ExportVisualizations

Constructor.

ExportVisualizations.Parameterizer - Class in de.lmu.ifi.dbs.elki.visualization

Parameterization class

ExportVisualizations.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.visualization.ExportVisualizations.Parameterizer

extend(SpatialComparable) - Method in class de.lmu.ifi.dbs.elki.data.ModifiableHyperBoundingBox

Extend the bounding box by some other spatial object.

extend(A, ArrayAdapter<T, A>, T) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ExtendedArray

Static wrapper that has a nicer generics signature.

ExtendedArray<T> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike

Class to extend an array with a single element virtually.

ExtendedArray(Object, ArrayAdapter<T, Object>, T) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ExtendedArray

Constructor.

ExtendedNeighborhood - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood

Neighborhood obtained by computing the k-fold closure of an existing neighborhood.

ExtendedNeighborhood(DataStore<DBIDs>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExtendedNeighborhood

Constructor.

ExtendedNeighborhood.Factory<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood

Factory class.

ExtendedNeighborhood.Factory(NeighborSetPredicate.Factory<O>, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExtendedNeighborhood.Factory

Constructor.

ExtendedNeighborhood.Factory.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood

Parameterization class.

ExtendedNeighborhood.Factory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExtendedNeighborhood.Factory.Parameterizer

extendMBR(SpatialComparable) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.SpatialDirectoryEntry

Extend the MBR of this node.

extendNeighborhood(Database, Relation<? extends O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExtendedNeighborhood.Factory

Method to load the external neighbors.

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

File name extension.

ExternalClustering - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.meta

Read an external clustering result from a file, such as produced by ClusteringVectorDumper.

ExternalClustering(File) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.meta.ExternalClustering

Constructor.

ExternalClustering.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.meta

Parameterization class

ExternalClustering.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.meta.ExternalClustering.Parameterizer

ExternalDoubleOutlierScore - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.meta

External outlier detection scores, loading outlier scores from an external file.

ExternalDoubleOutlierScore(File, Pattern, Pattern, boolean, ScalingFunction) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.ExternalDoubleOutlierScore

Constructor.

ExternalDoubleOutlierScore.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.meta

Parameterization class

ExternalDoubleOutlierScore.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.ExternalDoubleOutlierScore.Parameterizer

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

External ID objects.

ExternalID(String) - Constructor for class de.lmu.ifi.dbs.elki.data.ExternalID

Constructor.

EXTERNALID - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil

External ID type.

EXTERNALID_INDEX_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ExternalIDFilter.Parameterizer

Parameter that specifies the index of the label to be used as external Id, starting at 0.

ExternalIDFilter - Class in de.lmu.ifi.dbs.elki.datasource.filter.typeconversions

Class that turns a label column into an external ID column.

ExternalIDFilter(int) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ExternalIDFilter

Constructor.

ExternalIDFilter.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource.filter.typeconversions

Parameterization class.

ExternalIDFilter.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ExternalIDFilter.Parameterizer

externalIdIndex - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ExternalIDFilter

The index of the label to be used as external Id.

externalIdIndex - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ExternalIDFilter.Parameterizer

ExternalIDJoinDatabaseConnection - Class in de.lmu.ifi.dbs.elki.datasource

Joins multiple data sources by their label

ExternalIDJoinDatabaseConnection(List<ObjectFilter>, List<DatabaseConnection>) - Constructor for class de.lmu.ifi.dbs.elki.datasource.ExternalIDJoinDatabaseConnection

Constructor.

ExternalIDJoinDatabaseConnection.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource

Parameterization class.

ExternalIDJoinDatabaseConnection.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.datasource.ExternalIDJoinDatabaseConnection.Parameterizer

ExternalizablePage - Interface in de.lmu.ifi.dbs.elki.persistent

Base interface for externalizable pages.

ExternalNeighborhood - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood

A precomputed neighborhood, loaded from an external file.

ExternalNeighborhood(DataStore<DBIDs>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExternalNeighborhood

Constructor.

ExternalNeighborhood.Factory - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood

Factory class.

ExternalNeighborhood.Factory(File) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExternalNeighborhood.Factory

Constructor.

ExternalNeighborhood.Factory.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood

Parameterization class.

ExternalNeighborhood.Factory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExternalNeighborhood.Factory.Parameterizer

extra - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ExtendedArray

The extra element

extra - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.ItrAnc

Additional object to return as first result.

extra - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.ItrDesc

Additional object to return as first result.

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

Debugging flag: do extra integrity checks.

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

Development flag: This will enable some extra integrity checks on the tree.

extract(int, int, int, boolean, FPGrowth.FPTree.Collector) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPTree

Extract itemsets ending in the given item.

extract(int, int, int, int, int[], int, int[], int[], boolean, FPGrowth.FPTree.Collector) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPTree

Extract itemsets ending in the given item.

extractClusters(DBIDs, DBIDDataStore, DoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ExtractFlatClusteringFromHierarchy

Extract all clusters from the pi-lambda-representation.

extractClusters(DBIDs, DBIDDataStore, DoubleDataStore, DoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction

Extract all clusters from the pi-lambda-representation.

extractClusters(DBIDs, DBIDDataStore, DoubleDataStore, DoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction

Extract all clusters from the pi-lambda-representation.

extractClusters(ClusterOrder, Relation<?>, double, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSXi

Extract clusters from a cluster order result.

extractClusters(Relation<V>, DiSH.DiSHClusterOrder) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH

Extracts the clusters from the cluster order.

extractCorrelationClusters(Clustering<Model>, Relation<V>, int, ERiCNeighborPredicate<V>.Instance) - 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.

ExtractFlatClusteringFromHierarchy - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction

Extract a flat clustering from a full hierarchy, represented in pointer form.

ExtractFlatClusteringFromHierarchy(HierarchicalClusteringAlgorithm, int, boolean, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ExtractFlatClusteringFromHierarchy

Constructor.

ExtractFlatClusteringFromHierarchy(HierarchicalClusteringAlgorithm, double, boolean, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ExtractFlatClusteringFromHierarchy

Constructor.

ExtractFlatClusteringFromHierarchy.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction

Parameterization class.

ExtractFlatClusteringFromHierarchy.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ExtractFlatClusteringFromHierarchy.Parameterizer

ExtractFlatClusteringFromHierarchy.ThresholdMode - Enum in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction

Threshold mode.

ExtractFlatClusteringFromHierarchy.ThresholdMode() - Constructor for enum de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ExtractFlatClusteringFromHierarchy.ThresholdMode

ExtractFlatClusteringFromHierarchyEvaluator - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.extractor

Extract clusters from a hierarchical clustering, during the evaluation phase.

ExtractFlatClusteringFromHierarchyEvaluator(ExtractFlatClusteringFromHierarchy) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.extractor.ExtractFlatClusteringFromHierarchyEvaluator

Constructor.

ExtractFlatClusteringFromHierarchyEvaluator.DummyHierarchicalClusteringAlgorithm - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.extractor

Dummy instance.

ExtractFlatClusteringFromHierarchyEvaluator.DummyHierarchicalClusteringAlgorithm() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.extractor.ExtractFlatClusteringFromHierarchyEvaluator.DummyHierarchicalClusteringAlgorithm

Constructor.

ExtractFlatClusteringFromHierarchyEvaluator.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.extractor

Parameterization class.

ExtractFlatClusteringFromHierarchyEvaluator.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.extractor.ExtractFlatClusteringFromHierarchyEvaluator.Parameterizer

extractItemsets(DBIDs[], int, int, List<Itemset>) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.Eclat

extractItemsets(DBIDs, DBIDs[], int[], int, int, int, List<Itemset>) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.Eclat

extractLinear(int, int, int, int, int, int[], int, int[], FPGrowth.FPTree.Collector) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPTree

Extract itemsets from a linear tree.

extremum_alpha_n(int, double[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.ParameterizationFunction

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

extremumType - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.ParameterizationFunction

Holds the type of the global extremum.

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

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

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