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) - double[] 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.

EARLY_EXAGGERATION - Static variable in class de.lmu.ifi.dbs.elki.algorithm.projection.TSNE

Early exaggeration factor.

EARLY_EXAGGERATION_ITERATIONS - Static variable in class de.lmu.ifi.dbs.elki.algorithm.projection.TSNE

Number of iterations to apply early exaggeration.

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.

Edge(int, int) - Constructor for class de.lmu.ifi.dbs.elki.visualization.parallel3d.layout.Layout.Edge

Constructor.

edgelength(double[][], int[], int) - Static method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.MSTSplit

Length of edge i.

edges - Variable in class de.lmu.ifi.dbs.elki.visualization.parallel3d.layout.Layout

Edges

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.

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.

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.pca

Helper class which encapsulates an eigenvector and its corresponding eigenvalue.

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

Creates a new EigenPair object.

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

"absolute" Flag

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

Parameter delta

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

Parameter n

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

Parameter progressive alpha.

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

Parameter relative alpha.

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

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

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

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.

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

The eigenpairs in decreasing order.

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

The corresponding eigenvalue.

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

Eigenvalues and eigenvectors of a real matrix.

EigenvalueDecomposition(double[][]) - 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.

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

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.math.linearalgebra.Centroid

Vector elements.

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

The covariance matrix.

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

ELKIBuilder<T> - Class in de.lmu.ifi.dbs.elki.utilities

Builder utility class.

ELKIBuilder(Class<? super T>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIBuilder

Constructor.

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

Class to launch ELKI.

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

Private constructor.

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.

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

Class to iterate over a directory tree.

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(double[], double, double, double, double[]) - 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), with optional MAP regularization.

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

Constructor.

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

Constructor.

EM(int, double, EMClusterModelFactory<V, M>, int, double, 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_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.

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.

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(double[], double[][]) - 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.

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() - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.iterator.EmptyIterator

Get an empty hierarchy iterator.

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

Reusable empty array.

EMPTY_ARRAY - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseMinMaxNormalization

Empty double 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.DoubleIntegerDBIDArrayList

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.DoubleIntegerDBIDArrayList

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_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.io.ParseUtil

Preallocated exceptions.

EMPTY_VECTOR - Static variable in class de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution

Empty constant vector returned when no subspace was used.

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.

EmptyDataException - Exception in de.lmu.ifi.dbs.elki.utilities.exceptions

Exception thrown when a database / relation is empty.

EmptyDataException() - Constructor for exception de.lmu.ifi.dbs.elki.utilities.exceptions.EmptyDataException

Constructor.

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

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-

EmptyIterator<O> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.iterator

Empty object iterator.

EmptyIterator() - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.iterator.EmptyIterator

Private constructor, use static EmptyIterator.empty() instead.

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

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

Pattern to enable visualizers

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

Enable / disable the writer menu.

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.DoubleIntegerDBIDSubList

End offset.

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.datastructures.range.ExponentialIntGenerator

End value.

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.

END_VALUE - Static variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.iterator.IterableIt

End sentinel value.

endcg - Variable in class de.lmu.ifi.dbs.elki.application.greedyensemble.EvaluatePrecomputedOutlierScores

Normalization term E[NDCG].

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 steep area

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

End index

endsWith(CharSequence, CharSequence) - Static method in class de.lmu.ifi.dbs.elki.utilities.io.FormatUtil

Similar to String.endsWith(String) but for buffers.

endvec - Variable in class de.lmu.ifi.dbs.elki.visualization.parallel3d.util.Arcball1DOFAdapter

Ending point of drag.

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: \( 1-\prod_i(1-s_i) \)

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.

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.

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: \( \prod_i s_i \)

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.

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.evaluation.AutomaticEvaluation

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.SelectionResult

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.distribution.DistanceEntry

The entry of the Index.

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

Referenced entry

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

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

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.gdbscan.SimilarityNeighborPredicate

Range to query with

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

Range to query with

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

Minimum similarity threshold

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

Holds the epsilon radius threshold.

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

Holds the epsilon radius threshold.

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

Holds the epsilon radius threshold.

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

Maximum radius of the neighborhood to be considered.

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

Maximum radius of the neighborhood to be considered.

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.gdbscan.SimilarityNeighborPredicate.Parameterizer

Similarity threshold

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.Parameterizer

Maximum radius of the neighborhood to be considered.

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

Parameterization class

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.datastructures.BitsUtil

Test two bitsets for equality

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

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.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

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

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.

Use DBIDUtil.equal(de.lmu.ifi.dbs.elki.database.ids.DBIDRef, de.lmu.ifi.dbs.elki.database.ids.DBIDRef) instead.

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.ArcCosineUnitlengthDistanceFunction

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

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

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

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.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.CosineUnitlengthDistanceFunction

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.FileBasedSparseDoubleDistanceFunction

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

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.MatrixWeightedQuadraticDistanceFunction

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.LPIntegerNormDistanceFunction

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.WeightedLPNormDistanceFunction

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.FisherRaoDistanceFunction

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

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.TriangularDiscriminationDistanceFunction

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

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.set.HammingDistanceFunction

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

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

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

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.subspace.SubspaceEuclideanDistanceFunction

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

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

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

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.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.MTreeDirectoryEntry

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

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

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

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

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.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

equalsPlusTimes(double[], double[], double[], double) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization.Instance

Compute out = x + y * a, for 2d.

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.

ERF_COEFF1 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution

T.

ERF_COEFF2 - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution

T.

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

Complementary error function for Gaussian distributions = Normal distributions.

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

Inverse error function.

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

Gaussian Error Function Weight function, scaled using stddev.

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

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

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

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

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

Class to wrap the ERiC settings.

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

Parameterization class.

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.

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.VMath

Error message when dimensionalities do not agree.

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

Error message when min > max is given as a range.

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

Error message when matrix dimensionalities do not agree.

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

Error message when matrix dimensionalities do not agree.

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

Error when a non-square matrix is used with determinant.

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

When a symmetric positive definite matrix is required.

ERR_MATRIX_RANK_DEFICIENT - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.QRDecomposition

When a matrix is rank deficient.

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

When a matrix is rank deficient.

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

Error with a singular matrix.

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.VMath

Error message when vector dimensionalities do not agree.

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.

est - Variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta.BestFitEstimator.BestFit

Best estimator.

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

General form of the parameter estimation

estimate(double[]) - 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.ExpGammaExpMOMEstimator

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.InverseGaussianMLEstimator

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

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

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

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

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

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

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

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

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.WinsorizingEstimator

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

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

estimate(KNNQuery<?>, DBIDRef, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.ALIDEstimator

estimate(RangeQuery<?>, DBIDRef, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.ALIDEstimator

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

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

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

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

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

Estimate from a distance list.

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

Estimate from a Reference Point, a KNNQuery and the neighborhood size k.

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

Estimate from a distance list.

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

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

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

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

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

estimate(A, NumberArrayAdapter<?, ? super 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.

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

Estimate the (singed!)

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

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 interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogMeanVarianceEstimator

Estimate the distribution from mean and variance.

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.LogLogisticMADEstimator

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.LogGammaLogMOMEstimator

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

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.ExponentialMOMEstimator

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

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

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

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.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 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.EMGOlivierNorbergEstimator

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

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

General form of the parameter estimation

estimateID(DBIDRef, DoubleDBIDListIter, double[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.ISOS

Estimate the local intrinsic dimensionality.

estimateInitialBeta(DBIDRef, DoubleDBIDListIter, double) - Static method in class de.lmu.ifi.dbs.elki.algorithm.outlier.distance.SOS

Estimate beta from the distances in a row.

estimateInitialBeta(double[], double) - Static method in class de.lmu.ifi.dbs.elki.algorithm.projection.PerplexityAffinityMatrixBuilder

Estimate beta from the distances in a row.

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.

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

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

Estimate the log likelihood of a vector.

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

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

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

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

estimateThreshold(CFTree.TreeNode) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch.CFTree

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(double[][]) - 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.outlier.intrinsic.ISOS

Estimator of intrinsic dimensionality.

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

Estimator of intrinsic dimensionality.

estimator - Variable in class de.lmu.ifi.dbs.elki.algorithm.projection.IntrinsicNearestNeighborAffinityMatrixBuilder

Estimator of intrinsic dimensionality.

estimator - Variable in class de.lmu.ifi.dbs.elki.algorithm.projection.IntrinsicNearestNeighborAffinityMatrixBuilder.Parameterizer

Estimator of 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.outlier.intrinsic.ISOS.Parameterizer

Parameter for ID estimation.

ESTIMATOR_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.projection.IntrinsicNearestNeighborAffinityMatrixBuilder.Parameterizer

Parameter for ID estimation.

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.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

EU - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedExtremeValueLMMEstimator

Euler-Mascheroni constant.

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

Factor used for approximating circles with cubic beziers.

EuclideanDistanceCriterion - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch

Distance criterion.

EuclideanDistanceCriterion() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch.EuclideanDistanceCriterion

EuclideanDistanceCriterion.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch

Parameterization class

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.

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.

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

Euclidean length of the vector sqrt(v1^T v1).

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(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.DCGEvaluation

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.NDCGEvaluation

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

Evaluate given a list of positives and a scoring.

evaluateBy(ScoreEvaluation) - Method in class de.lmu.ifi.dbs.elki.result.outlier.OutlierResult

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.

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<O>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateDBCV

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

Result object for outlier score judgements.

evaluateClusters(ArrayList<PROCLUS.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.

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.

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

Compute the Density-Based Clustering Validation Index.

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

Constructor.

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

Parameterization class.

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

Output format

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

Parameterization class.

evaluateKNN(double[], ModifiableDoubleDBIDList, Relation<?>, Object2IntOpenHashMap<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.outlier.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 index of a clustering 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.

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(File, StreamingParser, 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.

evaluateRanking(ScoreEvaluation, Cluster<?>, DoubleDBIDList) - Static method in class de.lmu.ifi.dbs.elki.evaluation.clustering.EvaluateClustering

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

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.

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

Parameterization class.

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

Result object for MAP scores.

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.

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.

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.

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

Compute the Variance Ratio Criteria of a data set, also known as Calinski-Harabasz index.

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.

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

Constructor.

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

A group of evaluation measurements.

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<? extends 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.Parameterizer - Class in de.lmu.ifi.dbs.elki.workflow

Parameterization class.

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.

Event() - Constructor for enum de.lmu.ifi.dbs.elki.datasource.bundle.BundleStreamSource.Event

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.

EvolutionarySearch(Relation<V>, ArrayList<ArrayList<DBIDs>>, int, Random) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary.EvolutionarySearch

Constructor.

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

ewma - Variable in class de.lmu.ifi.dbs.elki.algorithm.timeseries.SigniTrendChangeDetection.Instance

Moving average and variance.

ewmv - Variable in class de.lmu.ifi.dbs.elki.algorithm.timeseries.SigniTrendChangeDetection.Instance

Moving average and variance.

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.

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

Delegate to FastMath.exp.

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

Observed value, minimum, maximum, expected value.

expandCluster(Relation<O>, RangeQuery<O>, DBIDRef, ArrayModifiableDBIDs, 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(DBIDRef, int, WritableIntegerDataStore, ModifiableDoubleDBIDList, ArrayModifiableDBIDs, RangeQuery<V>, FiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.GriDBSCAN.Instance

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

Expands the specified leaf nodes.

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

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

expandNodes(DeLiCluTree, SpatialPrimitiveDistanceFunction<V>, DeLiClu.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.DCGEvaluation

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.NDCGEvaluation

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.

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

Exp-Gamma Distribution, with random generation and density functions.

ExpGammaDistribution(double, double, double, Random) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExpGammaDistribution

Constructor for Gamma distribution.

ExpGammaDistribution(double, double, double, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExpGammaDistribution

Constructor for Gamma distribution.

ExpGammaDistribution(double, double, double) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExpGammaDistribution

Constructor for Gamma distribution.

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

Parameterization class

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

Simple parameter estimation for the ExpGamma distribution.

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

Private constructor.

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

Parameterization class.

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.AutotuningPCA.Cand

Score

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

The amount of Variance explained by strong Eigenvalues

EXPONENT_OVERFLOW - Static variable in class de.lmu.ifi.dbs.elki.utilities.io.ParseUtil

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

ExponentialIntGenerator - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.range

Generate an exponential range.

ExponentialIntGenerator(int, int, int) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.range.ExponentialIntGenerator

Constructor.

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.

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

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.

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.

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.

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

EXPONENTS_ID - Static variable in class tutorial.distancefunction.MultiLPNorm.Parameterizer

Option ID for the exponents

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

The "Export Image" button, to save the image

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

Class that automatically generates all visualizations and exports them into SVG files.

ExportVisualizations(File, VisualizerParameterizer, double, ExportVisualizations.Format) - Constructor for class de.lmu.ifi.dbs.elki.result.ExportVisualizations

Constructor.

ExportVisualizations(File, VisualizerParameterizer, double, ExportVisualizations.Format, int) - Constructor for class de.lmu.ifi.dbs.elki.result.ExportVisualizations

Constructor.

ExportVisualizations.Format - Enum in de.lmu.ifi.dbs.elki.result

File format

ExportVisualizations.Parameterizer - Class in de.lmu.ifi.dbs.elki.result

Parameterization class

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.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood

Parameterization class.

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

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

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.

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.

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.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood

Parameterization class.

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() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.AbstractCutDendrogram.Instance

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.

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[], 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.

ExtremumType() - Constructor for enum de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.ParameterizationFunction.ExtremumType

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