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

E

e - Variable in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel
Derived model parameters: e and e squared.
e - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenvalueDecomposition
Arrays for internal storage of eigenvalues.
e - Variable in class de.lmu.ifi.dbs.elki.math.statistics.MultipleLinearRegression
The (n x 1) - vector holding the estimated residuals (e1, ..., en)^T.
e - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.AttributeModifier
Provides the attribute to be modified.
e_czech - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredResult
The selection matrix of the strong eigenvectors.
e_hat - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredResult
The selection matrix of the weak eigenvectors.
EARTH_RADIUS - Static variable in class de.lmu.ifi.dbs.elki.math.geodesy.SphericalCosineEarthModel
Earth radius approximation in m.
EARTH_RADIUS - Static variable in class de.lmu.ifi.dbs.elki.math.geodesy.SphericalHaversineEarthModel
Earth radius approximation in m.
EARTH_RADIUS - Static variable in class de.lmu.ifi.dbs.elki.math.geodesy.SphericalVincentyEarthModel
Earth radius approximation in m.
EarthModel - Interface in de.lmu.ifi.dbs.elki.math.geodesy
API for handling different earth models.
ecefToLatDeg(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel
 
ecefToLatDeg(double, double, double) - Method in interface de.lmu.ifi.dbs.elki.math.geodesy.EarthModel
Convert a 3D coordinate pair to the corresponding latitude.
ecefToLatLngDegHeight(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel
 
ecefToLatLngDegHeight(double, double, double) - Method in interface de.lmu.ifi.dbs.elki.math.geodesy.EarthModel
Convert a 3D coordinate pair to the corresponding latitude, longitude and height.
ecefToLatLngRadHeight(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel
 
ecefToLatLngRadHeight(double, double, double) - Method in interface de.lmu.ifi.dbs.elki.math.geodesy.EarthModel
Convert a 3D coordinate pair to the corresponding latitude, longitude and height.
ecefToLatRad(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel
 
ecefToLatRad(double, double, double) - Method in interface de.lmu.ifi.dbs.elki.math.geodesy.EarthModel
Convert a 3D coordinate pair to the corresponding latitude.
ecefToLatRad(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.SphericalCosineEarthModel
 
ecefToLatRad(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.SphericalHaversineEarthModel
 
ecefToLatRad(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.SphericalVincentyEarthModel
 
ecefToLngDeg(double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel
 
ecefToLngDeg(double, double) - Method in interface de.lmu.ifi.dbs.elki.math.geodesy.EarthModel
Convert a 3D coordinate pair to the corresponding longitude.
ecefToLngRad(double, double) - Method in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel
 
ecefToLngRad(double, double) - Method in interface de.lmu.ifi.dbs.elki.math.geodesy.EarthModel
Convert a 3D coordinate pair to the corresponding longitude.
Eclat - Class in de.lmu.ifi.dbs.elki.algorithm.itemsetmining
Eclat is a depth-first discovery algorithm for mining frequent itemsets.
Eclat(double, int, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.Eclat
Constructor.
Eclat.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.itemsetmining
Parameterization class.
Eclat.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.Eclat.Parameterizer
 
edit - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.ClusterContingencyTable
Edit-Distance measures
EDIT_CLEAR - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon
 
EDIT_FIND - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon
 
EDIT_REDO - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon
 
EDIT_UNDO - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon
 
EditDistance - Class in de.lmu.ifi.dbs.elki.evaluation.clustering
Edit distance measures.
EditDistance(ClusterContingencyTable) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance
 
editDistanceFirst() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance
Get the editing distance to transform second clustering to first clustering (normalized, 0 = unequal)
editDistanceSecond() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance
Get the editing distance to transform second clustering to first clustering (normalized, 0 = unequal)
editFirst - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance
Edit operations for first clustering to second clustering.
editItem - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.ResultWindow.DynamicMenu
The "tabular edit" item.
editOperationsBaseline - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance
Baseline for edit operations
editOperationsBaseline() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance
Get the baseline editing Operations ( = total Objects)
editOperationsFirst() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance
Get the editing operations required to transform first clustering to second clustering
editOperationsSecond() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance
Get the editing operations required to transform second clustering to first clustering
editSecond - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.EditDistance
Edit operations for second clustering to first clustering.
EDRDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries
Edit Distance on Real Sequence distance for numerical vectors.
EDRDistanceFunction(double, double) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.EDRDistanceFunction
Constructor.
EDRDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries
Parameterization class.
EDRDistanceFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.EDRDistanceFunction.Parameterizer
 
effectiveBandSize(int, int) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.AbstractEditDistanceFunction
Compute the effective band size.
EigenPair - Class in de.lmu.ifi.dbs.elki.math.linearalgebra
Helper class which encapsulates an eigenvector and its corresponding eigenvalue.
EigenPair(Vector, double) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenPair
Creates a new EigenPair object.
EIGENPAIR_FILTER_ABSOLUTE - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.LimitEigenPairFilter
"absolute" Flag
EIGENPAIR_FILTER_COMPOSITE_LIST - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.CompositeEigenPairFilter
The list of filters to use.
EIGENPAIR_FILTER_DELTA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.LimitEigenPairFilter
Parameter delta
EIGENPAIR_FILTER_N - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.FirstNEigenPairFilter
Paremeter n
EIGENPAIR_FILTER_PALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.ProgressiveEigenPairFilter
Parameter progressive alpha.
EIGENPAIR_FILTER_RALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.RelativeEigenPairFilter
Parameter relative alpha.
EIGENPAIR_FILTER_WALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.WeakEigenPairFilter
EigenPairFilter - Interface in de.lmu.ifi.dbs.elki.math.linearalgebra.pca
The eigenpair filter is used to filter eigenpairs (i.e. eigenvectors and their corresponding eigenvalues) which are a result of a Variance Analysis Algorithm, e.g.
eigenPairFilter - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredRunner
Holds the instance of the EigenPairFilter specified by PCAFilteredRunner.Parameterizer.PCA_EIGENPAIR_FILTER.
eigenPairFilter - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredRunner.Parameterizer
Holds the instance of the EigenPairFilter specified by PCAFilteredRunner.Parameterizer.PCA_EIGENPAIR_FILTER.
eigenPairs - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAResult
The eigenpairs in decreasing order.
eigenPairs - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.SortedEigenPairs
The array of eigenpairs.
eigenvalue - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenPair
The corresponding eigenvalue.
EigenvalueDecomposition - Class in de.lmu.ifi.dbs.elki.math.linearalgebra
Eigenvalues and eigenvectors of a real matrix.
EigenvalueDecomposition(Matrix) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenvalueDecomposition
Check for symmetry, then construct the eigenvalue decomposition
eigenvalues - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAResult
The eigenvalues in decreasing order.
eigenValues() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.SortedEigenPairs
Returns the sorted eigenvalues.
eigenvector - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenPair
The eigenvector as a matrix.
eigenvectors - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAResult
The eigenvectors in decreasing order to their corresponding eigenvalues.
eigenVectors() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.SortedEigenPairs
Returns the sorted eigenvectors.
eigenVectors(int) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.SortedEigenPairs
Returns the first n sorted eigenvectors as a matrix.
element - Variable in class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea
Our element node.
elementCoordinatesFromEvent(Element, Event) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPlot
Convert screen coordinates to element coordinates.
elementCoordinatesFromEvent(Document, Element, Event) - Static method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGUtil
Convert the coordinates of an DOM Event from screen into element coordinates.
elementLine - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance
The line element
elementPoint - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance
The drag handle element
elements - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.MultivariateGaussianModel
Matrix element reference.
elements - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.CovarianceMatrix
The covariance matrix.
elements - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
Array for internal storage of elements.
elements - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector
Array for internal storage of elements.
elems - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy
All elements, in insertion order (and will not fail badly if concurrent insertions happen).
elemText - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance
The label element
ELKILauncher - Class in de.lmu.ifi.dbs.elki.application
Class to launch ELKI.
ELKILauncher() - Constructor for class de.lmu.ifi.dbs.elki.application.ELKILauncher
 
ELKILogRecord - Class in de.lmu.ifi.dbs.elki.logging
Base LogRecord class used in ELKI.
ELKILogRecord(Level, CharSequence) - Constructor for class de.lmu.ifi.dbs.elki.logging.ELKILogRecord
Constructor.
ELKIServiceLoader - Class in de.lmu.ifi.dbs.elki.utilities
Class that emulates the behavior of an java ServiceLoader, except that the classes are not automatically instantiated.
ELKIServiceLoader() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceLoader
Constructor - do not use.
ELKIServiceRegistry - Class in de.lmu.ifi.dbs.elki.utilities
Registry of available implementations in ELKI.
ELKIServiceRegistry() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry
Do not use constructor.
ELKIServiceRegistry.Entry - Class in de.lmu.ifi.dbs.elki.utilities
Entry in the service registry.
ELKIServiceRegistry.Entry() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry.Entry
 
ELKIServiceScanner - Class in de.lmu.ifi.dbs.elki.utilities
A collection of inspection-related utility functions.
ELKIServiceScanner() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner
Static methods only.
ELKIServiceScanner.ClassSorter - Class in de.lmu.ifi.dbs.elki.utilities
Sort classes by their class name.
ELKIServiceScanner.ClassSorter() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner.ClassSorter
 
ELKIServiceScanner.DirClassIterator - Class in de.lmu.ifi.dbs.elki.utilities
Class to iterate over a directory tree.
ELKIServiceScanner.DirClassIterator(File) - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceScanner.DirClassIterator
Constructor from Directory
ellipsoidVincentyFormulaDeg(double, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil
Compute the approximate great-circle distance of two points.
ellipsoidVincentyFormulaRad(double, double, double, double, double) - Static method in class de.lmu.ifi.dbs.elki.math.geodesy.SphereUtil
Compute the approximate great-circle distance of two points.
ellipticalArc(double, double, double, double, double, double, double) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPath
Elliptical arc curve to the given coordinates.
ellipticalArc(double, double, double, double, double, double[]) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPath
Elliptical arc curve to the given coordinates.
ellipticalArc(Vector, double, double, double, Vector) - Method in class de.lmu.ifi.dbs.elki.visualization.svg.SVGPath
Elliptical arc curve to the given coordinates.
EM<V extends NumberVector,M extends MeanModel> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.em
Clustering by expectation maximization (EM-Algorithm), also known as Gaussian Mixture Modeling (GMM).
EM(int, double, EMClusterModelFactory<V, M>, int, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.em.EM
Constructor.
em - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.EMOutlier.Parameterizer
EM clustering algorithm to run.
EM.Parameterizer<V extends NumberVector,M extends MeanModel> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.em
Parameterization class.
EM.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.em.EM.Parameterizer
 
EM_DELTA_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.P3C.Parameterizer
Threshold when to stop EM iterations.
embedOrThumbnail(int, PlotItem, VisualizationTask, Element) - Method in class de.lmu.ifi.dbs.elki.visualization.gui.overview.OverviewPlot
Produce thumbnail for a visualizer.
EMBLEM_IMPORTANT - Static variable in class de.lmu.ifi.dbs.elki.gui.icons.StockIcon
 
EMBORDER - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization.Instance
Generic tags to indicate the type of element.
emClustering - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.EMOutlier
Inner algorithm.
EMClusterModel<M extends MeanModel> - Interface in de.lmu.ifi.dbs.elki.algorithm.clustering.em
Models useable in EM clustering.
EMClusterModelFactory<V extends NumberVector,M extends MeanModel> - Interface in de.lmu.ifi.dbs.elki.algorithm.clustering.em
Factory for initializing the EM models.
EMClusterVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster
Visualizer for generating SVG-Elements containing ellipses for first, second and third standard deviation.
EMClusterVisualization() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization
Constructor
EMClusterVisualization.Instance - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster
Instance.
EMClusterVisualization.Instance(VisualizationTask, VisualizationPlot, double, double, Projection) - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster.EMClusterVisualization.Instance
Constructor
emDelta - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.P3C
Threshold when to stop EM iterations.
emDelta - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.P3C.Parameterizer
Threshold when to stop EM iterations.
EMGOlivierNorbergEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
Naive distribution estimation using mean and sample variance.
EMGOlivierNorbergEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.EMGOlivierNorbergEstimator
Private constructor, use static instance!
EMGOlivierNorbergEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
Parameterization class.
EMGOlivierNorbergEstimator.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.EMGOlivierNorbergEstimator.Parameterizer
 
EMModel - Class in de.lmu.ifi.dbs.elki.data.model
Cluster model of an EM cluster, providing a mean and a full covariance Matrix.
EMModel(Vector, Matrix) - Constructor for class de.lmu.ifi.dbs.elki.data.model.EMModel
Constructor.
EMOutlier<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.clustering
outlier detection algorithm using EM Clustering.
EMOutlier(EM<V, ?>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.EMOutlier
Constructor with an existing em clustering algorithm.
EMOutlier.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.clustering
Parameterization class.
EMOutlier.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.clustering.EMOutlier.Parameterizer
 
EMPTY - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.ArffParser
Empty line pattern.
EMPTY - Static variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.Rec
Empty list.
EMPTY_ALIASES - Static variable in class de.lmu.ifi.dbs.elki.utilities.ELKIServiceRegistry.Entry
Reusable empty array.
EMPTY_CHILDREN - Static variable in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPNode
Constant for leaf nodes.
EMPTY_DISTS - Static variable in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDList
Empty.
EMPTY_ENUMERATION - Variable in class de.lmu.ifi.dbs.elki.index.tree.BreadthFirstEnumeration
Represents an empty enumeration.
EMPTY_IDS - Static variable in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleIntegerDBIDList
Empty.
EMPTY_INTS - Static variable in class de.lmu.ifi.dbs.elki.math.MathUtil
Empty integer array.
EMPTY_ITERATOR - Static variable in class de.lmu.ifi.dbs.elki.database.ids.EmptyDBIDs
Empty DBID iterator.
EMPTY_ITERATOR - Static variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy
Empty iterator.
EMPTY_LABELS - Static variable in class de.lmu.ifi.dbs.elki.data.LabelList
Empty label list.
EMPTY_PAGE - Static variable in class de.lmu.ifi.dbs.elki.persistent.OnDiskArrayPageFile
Indicates an empty page.
EMPTY_PAGE - Static variable in class de.lmu.ifi.dbs.elki.persistent.PersistentPageFile
Indicates an empty page.
EMPTY_STRING - Static variable in class de.lmu.ifi.dbs.elki.utilities.FormatUtil
Preallocated exceptions.
EmptyDatabaseConnection - Class in de.lmu.ifi.dbs.elki.datasource
Pseudo database that is empty.
EmptyDatabaseConnection() - Constructor for class de.lmu.ifi.dbs.elki.datasource.EmptyDatabaseConnection
Constructor.
EMPTYDBIDS - Static variable in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
Final, global copy of empty DBIDs.
EmptyDBIDs - Class in de.lmu.ifi.dbs.elki.database.ids
Empty DBID collection.
EmptyDBIDs() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.EmptyDBIDs
Constructor.
EmptyDBIDs.EmptyDBIDIterator - Class in de.lmu.ifi.dbs.elki.database.ids
Iterator for empty DBIDs-
EmptyDBIDs.EmptyDBIDIterator() - Constructor for class de.lmu.ifi.dbs.elki.database.ids.EmptyDBIDs.EmptyDBIDIterator
 
emptyIterator() - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy
Get an empty hierarchy iterator.
emptyPages - Variable in class de.lmu.ifi.dbs.elki.persistent.AbstractStoringPageFile
A stack holding the empty page ids.
emptyPagesSize - Variable in class de.lmu.ifi.dbs.elki.index.tree.TreeIndexHeader
The number of bytes additionally needed for the listing of empty pages of the headed page file.
EmptyParameterization - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization
Parameterization handler that only allows the use of default values.
EmptyParameterization() - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.EmptyParameterization
 
enabled() - Method in interface de.lmu.ifi.dbs.elki.visualization.VisualizationMenuAction
Indicate if the menu option is enabled or greyed out.
enabled() - Method in interface de.lmu.ifi.dbs.elki.visualization.VisualizationMenuToggle
Indicate if the menu option is enabled or greyed out.
enabled() - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.actions.ClusterStyleAction.SetStyleAction
 
enableExport(boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.gui.ResultWindow.DynamicMenu
Enable / disable the export menu.
enableOverview(boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.gui.ResultWindow.DynamicMenu
Enable / disable the overview menu.
enableStart() - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea
Enable capturing of 'mousedown' events.
enableStop() - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea
Enable capturing of 'mousemove' and 'mouseup' events.
ENABLEVIS_ID - Static variable in class de.lmu.ifi.dbs.elki.visualization.VisualizerParameterizer.Parameterizer
Parameter to enable visualizers Key: -vis.enable Default: ELKI core
enableVisualizers - Variable in class de.lmu.ifi.dbs.elki.visualization.VisualizerParameterizer.Parameterizer
Pattern to enable visualizers
encoder - Variable in class de.lmu.ifi.dbs.elki.utilities.io.ByteArrayUtil.StringSerializer
Encoder.
end - Variable in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs.Slice
Slice positions.
end - Variable in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs.Slice
Slice positions.
end - Variable in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDPair.Slice
Slice positions.
end() - Method in interface de.lmu.ifi.dbs.elki.logging.statistics.Duration
Finish the timer.
end - Variable in class de.lmu.ifi.dbs.elki.logging.statistics.MillisTimeDuration
Tracking variables.
end() - Method in class de.lmu.ifi.dbs.elki.logging.statistics.MillisTimeDuration
 
end - Variable in class de.lmu.ifi.dbs.elki.logging.statistics.NanoDuration
Tracking variables.
end() - Method in class de.lmu.ifi.dbs.elki.logging.statistics.NanoDuration
 
end - Variable in class de.lmu.ifi.dbs.elki.parallel.ParallelExecutor.BlockArrayRunner
End position
end - Variable in class de.lmu.ifi.dbs.elki.utilities.io.LineReader
Current position, and length of buffer
end - Variable in class de.lmu.ifi.dbs.elki.utilities.io.Tokenizer
Current positions of result and iterator.
endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in interface de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea.DragListener
Method called when a drag was ended.
endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.DragableArea
Method called when a drag was ended.
endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance
 
endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotSelectionVisualization.Instance
 
endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolAxisRangeVisualization.Instance
 
endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolLineVisualization.Instance
 
endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.MoveObjectsToolVisualization.Instance
 
endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolCubeVisualization.Instance
 
endDrag(SVGPoint, SVGPoint, Event, boolean) - Method in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolDotVisualization.Instance
 
endindex - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSXi.SteepArea
End index of down-area
endIndex - Variable in class de.lmu.ifi.dbs.elki.data.model.OPTICSModel
End index
enlargement(SpatialComparable, SpatialComparable) - Static method in class de.lmu.ifi.dbs.elki.data.spatial.SpatialUtil
Compute the enlargement obtained by adding an object to an existing object.
enlargementScaled(SpatialComparable, SpatialComparable, double) - Static method in class de.lmu.ifi.dbs.elki.data.spatial.SpatialUtil
Compute the enlargement obtained by adding an object to an existing object.
EnsembleEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality
Ensemble estimator taking the median of three of our best estimators.
EnsembleEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.EnsembleEstimator
 
EnsembleVoting - Interface in de.lmu.ifi.dbs.elki.utilities.ensemble
Interface for ensemble voting rules
EnsembleVotingInverseMultiplicative - Class in de.lmu.ifi.dbs.elki.utilities.ensemble
Inverse multiplicative voting: 1-product(1-s_i)
EnsembleVotingInverseMultiplicative() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingInverseMultiplicative
Constructor.
EnsembleVotingInverseMultiplicative.Parameterizer - Class in de.lmu.ifi.dbs.elki.utilities.ensemble
Parameterization class.
EnsembleVotingInverseMultiplicative.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingInverseMultiplicative.Parameterizer
 
EnsembleVotingMax - Class in de.lmu.ifi.dbs.elki.utilities.ensemble
Simple combination rule, by taking the maximum.
EnsembleVotingMax() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMax
Constructor.
EnsembleVotingMean - Class in de.lmu.ifi.dbs.elki.utilities.ensemble
Simple combination rule, by taking the mean
EnsembleVotingMean() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMean
Constructor.
EnsembleVotingMedian - Class in de.lmu.ifi.dbs.elki.utilities.ensemble
Simple combination rule, by taking the median.
EnsembleVotingMedian(double) - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMedian
Constructor.
EnsembleVotingMedian.Parameterizer - Class in de.lmu.ifi.dbs.elki.utilities.ensemble
Parameterization class.
EnsembleVotingMedian.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMedian.Parameterizer
 
EnsembleVotingMin - Class in de.lmu.ifi.dbs.elki.utilities.ensemble
Simple combination rule, by taking the minimum.
EnsembleVotingMin() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMin
Constructor.
EnsembleVotingMultiplicative - Class in de.lmu.ifi.dbs.elki.utilities.ensemble
Inverse multiplicative voting: product(s_i)
EnsembleVotingMultiplicative() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMultiplicative
Constructor.
EnsembleVotingMultiplicative.Parameterizer - Class in de.lmu.ifi.dbs.elki.utilities.ensemble
Parameterization class.
EnsembleVotingMultiplicative.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.utilities.ensemble.EnsembleVotingMultiplicative.Parameterizer
 
ensureArray(DBIDs) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
Ensure that the given DBIDs are array-indexable.
ensureBuffer(int, ByteBuffer, WritableByteChannel) - Method in class de.lmu.ifi.dbs.elki.datasource.bundle.BundleWriter
Ensure the buffer is large enough.
ensureClusteringResult(Database, Result) - Static method in class de.lmu.ifi.dbs.elki.result.ResultUtil
Ensure that the result contains at least one Clustering.
ensureCompleted(FiniteProgress) - Method in class de.lmu.ifi.dbs.elki.logging.Logging
Increment a progress (unless null).
ensureCompleted(Logging) - Method in class de.lmu.ifi.dbs.elki.logging.progress.FiniteProgress
Ensure that the progress was completed, to make progress bars disappear
ensureModifiable(DBIDs) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
Ensure modifiable.
ensureSelectionResult(Database) - Static method in class de.lmu.ifi.dbs.elki.result.ResultUtil
Ensure that there also is a selection container object.
ensureSet(DBIDs) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
Ensure that the given DBIDs support fast "contains" operations.
ensureSize() - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPNode
Ensure we have enough storage.
ensureSize(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayModifiableIntegerDBIDs
Resize as desired.
ensureSize(int) - Method in class de.lmu.ifi.dbs.elki.persistent.OnDiskArray
Ensure that the file can fit the given number of records.
entries - Variable in class de.lmu.ifi.dbs.elki.index.tree.AbstractNode
The entries (children) of this node.
entries - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.strategies.split.TopologicalSplitter.Split
The entries we process.
entropy - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.ClusterContingencyTable
Entropy-based measures
Entropy - Class in de.lmu.ifi.dbs.elki.evaluation.clustering
Entropy based measures.
Entropy(ClusterContingencyTable) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Constructor.
entropyConditionalFirst() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Get the conditional entropy of the first clustering.
entropyConditionalSecond() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Get the conditional entropy of the first clustering.
entropyFirst - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Entropy in first
entropyFirst() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Get the entropy of the first clustering using Log_2.
entropyJoint - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Joint entropy
entropyJoint() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Get the joint entropy of both clusterings (not normalized, 0 = equal)
entropyMutualInformation() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Get the mutual information (not normalized, 0 = equal)
entropyNMIJoint() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Get the joint-normalized mutual information (normalized, 0 = unequal)
entropyNMIMax() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Get the max-normalized mutual information (normalized, 0 = unequal)
entropyNMIMin() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Get the min-normalized mutual information (normalized, 0 = unequal)
entropyNMISqrt() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Get the sqrt-normalized mutual information (normalized, 0 = unequal)
entropyNMISum() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Get the sum-normalized mutual information (normalized, 0 = unequal)
entropyPowers() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Get Powers entropy (normalized, 0 = equal) Powers = 1 - NMI_Sum
entropySecond - Variable in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Entropy in second
entropySecond() - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.Entropy
Get the entropy of the second clustering using Log_2.
Entry - Interface in de.lmu.ifi.dbs.elki.index.tree
Defines the requirements for an entry in an index structure.
entry - Variable in class de.lmu.ifi.dbs.elki.index.tree.IndexTreePath
The entry of this component.
entry - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split.DistanceEntry
The entry of the Index.
entry - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.RStarTreeKNNQuery.DoubleDistanceEntry
Referenced entry
entry1 - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.DeLiClu.SpatialObjectPair
The first entry of this pair.
entry2 - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.DeLiClu.SpatialObjectPair
The second entry of this pair.
entrySet() - Method in class de.lmu.ifi.dbs.elki.visualization.gui.overview.RectangleArranger
The items contained in the map.
enumClass - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.EnumParameter
Reference to the actual enum type, for T.valueOf().
EnumParameter<E extends Enum<E>> - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters
Parameter class for a parameter specifying an enum type.
EnumParameter(OptionID, Class<E>, E) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.EnumParameter
Constructs an enum parameter with the given optionID, constraints and default value.
EnumParameter(OptionID, Class<E>, boolean) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.EnumParameter
Constructs an enum parameter with the given optionID, constraints and default value.
EnumParameter(OptionID, Class<E>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.EnumParameter
Constructs an enum parameter with the given optionID, constraints and default value.
EnumParameterConfigurator - Class in de.lmu.ifi.dbs.elki.gui.configurator
Panel to configure EnumParameters by offering a dropdown to choose from.
EnumParameterConfigurator(EnumParameter<?>, JComponent) - Constructor for class de.lmu.ifi.dbs.elki.gui.configurator.EnumParameterConfigurator
 
EpanechnikovKernelDensityFunction - Class in de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions
Epanechnikov kernel density estimator.
EpanechnikovKernelDensityFunction() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.EpanechnikovKernelDensityFunction
Private, empty constructor.
EpanechnikovKernelDensityFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions
Parameterization stub.
EpanechnikovKernelDensityFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.kernelfunctions.EpanechnikovKernelDensityFunction.Parameterizer
 
eps - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.OUTRES
The epsilon (in 2d) parameter
eps - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.OUTRES.Parameterizer
Query radius
EPS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenvalueDecomposition
Epsilon.
EPS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.SingularValueDecomposition
 
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.COPAC.Settings
Epsilon value for GDBSCAN.
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.FourC.Settings
Query radius epsilon.
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN
Holds the epsilon radius threshold.
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN.Parameterizer
Holds the epsilon radius threshold.
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.AbstractRangeQueryNeighborPredicate
Range to query with.
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.AbstractRangeQueryNeighborPredicate.Parameterizer
Range to query with
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.EpsilonNeighborPredicate
Range to query with
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.EpsilonNeighborPredicate.Instance
Range to query with
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.EpsilonNeighborPredicate.Parameterizer
Range to query with
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.AbstractOPTICS
Holds the maximum distance to search for objects (performance parameter)
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.AbstractOPTICS.Parameterizer
Epsilon radius.
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.SNNClustering
Epsilon radius threshold.
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.SNNClustering.Parameterizer
 
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH
Holds the value of DiSH.Parameterizer.EPSILON_ID.
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.Parameterizer
 
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PreDeCon.Settings
Query radius parameter epsilon.
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.SUBCLU
Holds the value of SUBCLU.EPSILON_ID.
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.SUBCLU.Parameterizer
 
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.FDBSCAN.Parameterizer
Epsilon radius
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.FDBSCANNeighborPredicate
Epsilon radius
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.FDBSCANNeighborPredicate.Instance
The epsilon distance a neighbor may have at most.
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.FDBSCANNeighborPredicate.Parameterizer
Epsilon radius
epsilon - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex
The epsilon value for each dimension.
epsilon - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex.Factory
The epsilon value for each dimension.
epsilon - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex.Factory.Parameterizer
The epsilon value for each dimension.
epsilon - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance
The current epsilon value.
EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN.Parameterizer
Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to the distance function specified.
EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.AbstractOPTICS.Parameterizer
Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to the distance function specified.
EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.SNNClustering.Parameterizer
Parameter to specify the minimum SNN density, must be an integer greater than 0.
EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.Parameterizer
Parameter that specifies the maximum radius of the neighborhood to be considered in each dimension for determination of the preference vector, must be a double equal to or greater than 0.
EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.HiSC.Parameterizer
Parameter to specify the maximum distance between two vectors with equal preference vectors before considering them as parallel, must be a double equal to or greater than 0.
EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.SUBCLU
Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to DimensionSelectingSubspaceDistanceFunction.
EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.preference.DiSHPreferenceVectorIndex.Factory
A comma separated list of positive doubles specifying the maximum radius of the neighborhood to be considered in each dimension for determination of the preference vector (default is DiSHPreferenceVectorIndex.Factory.DEFAULT_EPSILON in each dimension).
EpsilonNeighborPredicate<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan
The default DBSCAN and OPTICS neighbor predicate, using an epsilon-neighborhood.
EpsilonNeighborPredicate(double, DistanceFunction<? super O>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.EpsilonNeighborPredicate
Full constructor.
EpsilonNeighborPredicate.Instance - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan
Instance for a particular data set.
EpsilonNeighborPredicate.Instance(double, RangeQuery<?>, DBIDs) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.EpsilonNeighborPredicate.Instance
Constructor.
EpsilonNeighborPredicate.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan
Parameterization class
EpsilonNeighborPredicate.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.EpsilonNeighborPredicate.Parameterizer
 
epsilons - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.OUTRES.KernelDensityEstimator
Epsilon values for different subspace dimensionalities
epsilonsq - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.COPACNeighborPredicate
Squared value of epsilon.
epsilonsq - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.FDBSCANNeighborPredicate.Instance
The epsilon distance a neighbor may have at most.
equal(DBIDRef, DBIDRef) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDFactory
Compare two DBIDs, for equality testing.
equal(DBIDRef, DBIDRef) - Static method in class de.lmu.ifi.dbs.elki.database.ids.DBIDUtil
Test two DBIDs for equality.
equal(DBIDRef, DBIDRef) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.AbstractIntegerDBIDFactory
 
equal(long[], long[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.BitsUtil
Test two bitsets for equality
equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.CASHInterval
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.DeLiClu.SpatialObjectPair
equals is used in updating the heap!
equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSHeapEntry
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.DenseItemset
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.OneItemset
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.SmallDenseItemset
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.SparseItemset
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.subspace.AggarwalYuEvolutionary.Individuum
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.data.BitVector
Indicates whether some other object is "equal to" this BitVector.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.data.ClassLabel
Any ClassLabel should ensure a natural ordering that is consistent with equals.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.data.ExternalID
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.data.HyperBoundingBox
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.data.SimpleClassLabel
Any ClassLabel should ensure a natural ordering that is consistent with equals.
equals(SpatialComparable, SpatialComparable) - Static method in class de.lmu.ifi.dbs.elki.data.spatial.SpatialUtil
Test two SpatialComparables for equality.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.data.Subspace
Indicates if the specified object is equal to this subspace, i.e. if the specified object is a Subspace and is built of the same dimensions than this subspace.
equals(Object) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBID
Deprecated.
equals(Object) - Method in interface de.lmu.ifi.dbs.elki.database.ids.DBIDRef
Deprecated.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.database.ids.EmptyDBIDs.EmptyDBIDIterator
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.ArrayStaticIntegerDBIDs.Itr
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBID
Deprecated.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBID.Itr
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDPair
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDRange.Itr
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.IntegerDBIDVar.Itr
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.adapter.AbstractSimilarityAdapter
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.ArcCosineDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram.HistogramIntersectionDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram.HSBHistogramQuadraticDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.colorhistogram.RGBHistogramQuadraticDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.AbsolutePearsonCorrelationDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.AbsoluteUncenteredCorrelationDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.PearsonCorrelationDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.SquaredPearsonCorrelationDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.SquaredUncenteredCorrelationDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.UncenteredCorrelationDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.WeightedPearsonCorrelationDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.WeightedSquaredPearsonCorrelationDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.CosineDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedDoubleDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.DiskCacheBasedFloatDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.FileBasedDoubleDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.external.FileBasedFloatDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.geo.DimensionSelectingLatLngDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.geo.LatLngDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.geo.LngLatDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.histogram.HistogramMatchDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.histogram.KolmogorovSmirnovDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.EuclideanDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.LPNormDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.ManhattanDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.MaximumDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.MinimumDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.SquaredEuclideanDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedEuclideanDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedLPNormDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedManhattanDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedMaximumDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.WeightedSquaredEuclideanDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.ChiSquaredDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.JeffreyDivergenceDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.KullbackLeiblerDivergenceAsymmetricDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.KullbackLeiblerDivergenceReverseAsymmetricDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.probabilistic.SqrtJensenShannonDivergenceDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.RandomStableDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.AbstractDimensionsSelectingDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.OnedimensionalDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.AbstractEditDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.EDRDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.ERPDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.LCSSDistanceFunction
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments.Segment
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.DistanceResultAdapter
Deprecated.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.FilteredDistanceResultAdapter
Deprecated.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.OutlierScoreAdapter
Deprecated.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.adapter.SimpleAdapter
Deprecated.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.AbstractDirectoryEntry
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.AbstractLeafEntry
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.AbstractNode
Returns true if this == o has the value true or o is not null and o is of the same class as this instance and super.equals(o) returns true and both nodes are of the same type (leaf node or directory node) and have contain the same entries, false otherwise.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.IndexTreePath
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.ApproximationLine
Returns true if this object is the same as the o argument; false otherwise.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPDirectoryEntry
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop.MkCoPLeafEntry
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxDirectoryEntry
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax.MkMaxLeafEntry
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabDirectoryEntry
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab.MkTabLeafEntry
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.MTreeDirectoryEntry
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.MTreeLeafEntry
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.query.DoubleDistanceSearchCandidate
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.query.GenericMTreeDistanceSearchCandidate
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNDirectoryEntry
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rdknn.RdKNNLeafEntry
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector
 
equals(double[], double[]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
Compare for equality.
equals(double[][], double[][]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
Test for equality
equals(Object) - Method in class de.lmu.ifi.dbs.elki.persistent.AbstractExternalizablePage
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.DoublePriorityObject
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.datastructures.heap.IntegerPriorityObject
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.DoubleDoublePair
Trivial equals implementation
equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.DoubleIntPair
Trivial equals implementation
equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.DoubleObjPair
 
equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.IntDoublePair
Trivial equals implementation
equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.IntIntPair
Trivial equals implementation
equals(Object) - Method in class de.lmu.ifi.dbs.elki.utilities.pairs.Pair
Simple equals statement.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.visualization.VisualizationTask
 
EqualSizeGlobalConstraint - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints
Global parameter constraint defining that a number of list parameters ( ListParameter ) must have equal list sizes.
EqualSizeGlobalConstraint(ListParameter<?, ?>...) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.EqualSizeGlobalConstraint
Creates a global parameter constraint for testing if a number of list parameters have equal list sizes.
EqualStringConstraint - Class in de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints
Represents a parameter constraint for testing if the string value of the string parameter ( StringParameter ) to be tested is equal to the specified constraint-strings.
EqualStringConstraint(String[]) - Constructor for class de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.EqualStringConstraint
Creates an Equal-To-String parameter constraint.
equationsToString(String, int) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem
Returns a string representation of this equation system.
equationsToString(String, NumberFormat) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem
Returns a string representation of this equation system.
equationsToString(NumberFormat) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem
Returns a string representation of this equation system.
equationsToString(int) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem
Returns a string representation of this equation system.
erf(double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
Error function for Gaussian distributions = Normal distributions.
ERFAPP_A - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
Coefficients for erf approximation.
ERFAPP_B - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
Coefficients for erf approximation.
ERFAPP_C - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
Coefficients for erf approximation.
ERFAPP_D - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
Coefficients for erf approximation.
ERFAPP_P - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
Coefficients for erf approximation.
ERFAPP_Q - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
Coefficients for erf approximation.
erfc(double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
Complementary error function for Gaussian distributions = Normal distributions.
ErfcStddevWeight - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions
Gaussian Error Function Weight function, scaled using stddev.
ErfcStddevWeight() - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions.ErfcStddevWeight
 
ErfcWeight - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions
Gaussian Error Function Weight function, scaled such that the result it 0.1 at distance == max erfc(1.1630871536766736 * distance / max) The value of 1.1630871536766736 is erfcinv(0.1), to achieve the intended scaling.
ErfcWeight() - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions.ErfcWeight
 
erfinv(double) - Static method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
Inverse error function.
ERFINV_A - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
Coefficients for erfinv approximation, rational version
ERFINV_B - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
Coefficients for erfinv approximation, rational version
ERFINV_C - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
Coefficients for erfinv approximation, rational version
ERFINV_D - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution
Coefficients for erfinv approximation, rational version
ERiC<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation
Performs correlation clustering on the data partitioned according to local correlation dimensionality and builds a hierarchy of correlation clusters that allows multiple inheritance from the clustering result.
ERiC(ERiC.Settings) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ERiC
Constructor.
ERiC.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation
Parameterization class.
ERiC.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ERiC.Parameterizer
 
ERiC.Settings - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation
Class to wrap the ERiC settings.
ERiC.Settings() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ERiC.Settings
 
ERiC.Settings.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation
Parameterization class.
ERiC.Settings.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ERiC.Settings.Parameterizer
 
ERiCNeighborPredicate<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan
ERiC neighborhood predicate.
ERiCNeighborPredicate(ERiC.Settings) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.ERiCNeighborPredicate
Constructor.
ERiCNeighborPredicate.Instance - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan
Instance for a particular data set.
ERiCNeighborPredicate.Instance(DBIDs, DataStore<PCAFilteredResult>, Relation<? extends NumberVector>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.ERiCNeighborPredicate.Instance
Constructor.
ERiCNeighborPredicate.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan
Parameterization class.
ERiCNeighborPredicate.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.ERiCNeighborPredicate.Parameterizer
 
ERPDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries
Edit Distance With Real Penalty distance for numerical vectors.
ERPDistanceFunction(double, double) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.ERPDistanceFunction
Constructor.
ERPDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries
Parameterization class.
ERPDistanceFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries.ERPDistanceFunction.Parameterizer
 
err - Variable in class de.lmu.ifi.dbs.elki.logging.CLISmartHandler
Output stream for error output.
ERR_DIMENSIONS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector
Error message (in assertions!)
ERR_DIMENSIONS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
Error message (in assertions!)
ERR_MATRIX_DIMENSIONS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
Error when matrix dimensions do not agree.
ERR_MATRIX_DIMENSIONS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
Error message (in assertions!)
ERR_MATRIX_INNERDIM - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
Error when matrix inner dimensions do not agree.
ERR_MATRIX_INNERDIM - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector
Error message (in assertions!)
ERR_MATRIX_INNERDIM - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
Error message (in assertions!)
ERR_NOTRECTANGULAR - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
Error: matrix not rectangular.
ERR_REINDEX - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
Error: matrix indexes incorrect
ERR_TOO_LITTLE_WEIGHT - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.CovarianceMatrix
Error message reported when too little data (weight <= 1) in matrix.
ERR_VEC_DIMENSIONS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector
Error message (in assertions!)
ERR_VEC_DIMENSIONS - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
Error message (in assertions!)
errformat - Variable in class de.lmu.ifi.dbs.elki.gui.util.LogPane
Formatter for error messages
errformat - Variable in class de.lmu.ifi.dbs.elki.logging.CLISmartHandler
Formatter for error messages
error(CharSequence, Throwable) - Method in class de.lmu.ifi.dbs.elki.logging.Logging
Log a message at the 'severe' level.
error(CharSequence) - Method in class de.lmu.ifi.dbs.elki.logging.Logging
Log a message at the 'severe' level.
ErrorFormatter - Class in de.lmu.ifi.dbs.elki.logging
Format a log record for error output, including a stack trace if available.
ErrorFormatter() - Constructor for class de.lmu.ifi.dbs.elki.logging.ErrorFormatter
Constructor.
errors - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.AbstractParameterization
Errors
errors - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.UnParameterization
Errors
errorsTo(Parameterization) - Method in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ChainedParameterization
Set the error target, since there is no unique way where errors can be reported.
errorTarget - Variable in class de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ChainedParameterization
Error target
errorVector(V) - Method in class de.lmu.ifi.dbs.elki.data.model.CorrelationAnalysisSolution
Returns the error vectors after projection.
errStyle - Variable in class de.lmu.ifi.dbs.elki.gui.util.LogPane
Error message style
esq - Variable in class de.lmu.ifi.dbs.elki.math.geodesy.AbstractEarthModel
Derived model parameters: e and e squared.
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractExpMADEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLMMEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMADEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMeanVarianceEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMOMEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMADEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMeanVarianceEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMOMEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.DistributionEstimator
General form of the parameter estimation
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GammaChoiWetteEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LaplaceMLEEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogGammaChoiWetteEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogNormalLevenbergMarquardtKDEEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta.BestFitEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta.TrimmedEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.meta.WinsorisingEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.NormalLevenbergMarquardtKDEEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.RayleighMLEEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.UniformEnhancedMinMaxEstimator
 
estimate(double, double, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.UniformEnhancedMinMaxEstimator
Estimate from simple characteristics.
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.UniformMinMaxEstimator
 
estimate(DoubleMinMax) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.UniformMinMaxEstimator
Estimate parameters from minimum and maximum observed.
estimate(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.UniformMinMaxEstimator
Estimate parameters from minimum and maximum observed.
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.WaldMLEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.WeibullLogMOMEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.AbstractIntrinsicDimensionalityEstimator
 
estimate(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.AbstractIntrinsicDimensionalityEstimator
 
estimate(double[], int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.AbstractIntrinsicDimensionalityEstimator
 
estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.AggregatedHillEstimator
 
estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.EnsembleEstimator
 
estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.GEDEstimator
 
estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.HillEstimator
 
estimate(A, NumberArrayAdapter<?, A>) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.IntrinsicDimensionalityEstimator
Estimate from a distance list.
estimate(A, NumberArrayAdapter<?, A>, int) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.IntrinsicDimensionalityEstimator
Estimate from a distance list.
estimate(double[]) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.IntrinsicDimensionalityEstimator
Estimate from a distance list.
estimate(double[], int) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.IntrinsicDimensionalityEstimator
Estimate from a distance list.
estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.LMomentsEstimator
 
estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.MOMEstimator
 
estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.PWM2Estimator
 
estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.PWMEstimator
 
estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.RVEstimator
 
estimate(A, NumberArrayAdapter<?, A>, int) - Method in class de.lmu.ifi.dbs.elki.math.statistics.intrinsicdimensionality.ZipfEstimator
 
estimateDensities(Relation<O>, KNNQuery<O>, DBIDs, WritableDataStore<double[]>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.KDEOS
Perform the kernel density estimation step.
estimateDensity(NumberVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.DiagonalGaussianModel
 
estimateDensity(NumberVector) - Method in interface de.lmu.ifi.dbs.elki.algorithm.clustering.em.EMClusterModel
Estimate the likelihood of a vector.
estimateDensity(NumberVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.MultivariateGaussianModel
 
estimateDensity(NumberVector) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.em.SphericalGaussianModel
 
estimateEigenvalue(double[][], double[]) - Method in class de.lmu.ifi.dbs.elki.datasource.filter.transform.FastMultidimensionalScalingTransform
Estimate the (singed!)
estimateFromExpMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractExpMADEstimator
 
estimateFromExpMedianMAD(double, double) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExpMADDistributionEstimator
General form of the parameter estimation
estimateFromExpMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogGammaAlternateExpMADEstimator
 
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLMMEstimator
 
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialLMMEstimator
 
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GammaLMMEstimator
 
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedExtremeValueLMMEstimator
 
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedLogisticAlternateLMMEstimator
 
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GeneralizedParetoLMMEstimator
 
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GumbelLMMEstimator
 
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LaplaceLMMEstimator
 
estimateFromLMoments(double[]) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LMMDistributionEstimator
Estimate from the L-Moments.
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogisticLMMEstimator
 
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogNormalBilkovaLMMEstimator
 
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogNormalLMMEstimator
 
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.NormalLMMEstimator
 
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.RayleighLMMEstimator
 
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.SkewGNormalLMMEstimator
 
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.UniformLMMEstimator
 
estimateFromLMoments(double[]) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.WeibullLMMEstimator
 
estimateFromLogMeanVariance(MeanVariance, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMeanVarianceEstimator
Estimate the distribution from mean and variance.
estimateFromLogMeanVariance(MeanVariance, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogGammaLogMOMEstimator
 
estimateFromLogMeanVariance(MeanVariance, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogNormalLogMOMEstimator
 
estimateFromLogMedianMAD(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMADEstimator
 
estimateFromLogMedianMAD(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogGammaLogMADEstimator
 
estimateFromLogMedianMAD(double, double, double) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogMADDistributionEstimator
General form of the parameter estimation
estimateFromLogMedianMAD(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogNormalLogMADEstimator
 
estimateFromLogMedianMAD(double, double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.WeibullLogMADEstimator
 
estimateFromLogStatisticalMoments(StatisticalMoments, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMeanVarianceEstimator
 
estimateFromLogStatisticalMoments(StatisticalMoments, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractLogMOMEstimator
 
estimateFromLogStatisticalMoments(StatisticalMoments, double) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogMOMDistributionEstimator
General form of the parameter estimation
estimateFromMeanVariance(MeanVariance) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMeanVarianceEstimator
 
estimateFromMeanVariance(MeanVariance) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMOMEstimator
 
estimateFromMeanVariance(MeanVariance) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GammaMOMEstimator
 
estimateFromMeanVariance(MeanVariance) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.MeanVarianceDistributionEstimator
Estimate the distribution from mean and variance.
estimateFromMeanVariance(MeanVariance) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.NormalMOMEstimator
 
estimateFromMeanVariance(MeanVariance) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.WaldMOMEstimator
 
estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMADEstimator
 
estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.CauchyMADEstimator
 
estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMADEstimator
 
estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMedianEstimator
 
estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GammaMADEstimator
 
estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.GumbelMADEstimator
 
estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LaplaceMADEstimator
 
estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogisticMADEstimator
 
estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.LogLogisticMADEstimator
 
estimateFromMedianMAD(double, double) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.MADDistributionEstimator
General form of the parameter estimation
estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.NormalMADEstimator
 
estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.RayleighMADEstimator
 
estimateFromMedianMAD(double, double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.UniformMADEstimator
 
estimateFromStatisticalMoments(StatisticalMoments) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMeanVarianceEstimator
 
estimateFromStatisticalMoments(StatisticalMoments) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.AbstractMOMEstimator
 
estimateFromStatisticalMoments(StatisticalMoments) - Method in class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.EMGOlivierNorbergEstimator
 
estimateFromStatisticalMoments(StatisticalMoments) - Method in interface de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.MOMDistributionEstimator
General form of the parameter estimation
EstimateIntrinsicDimensionality<O> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics
Estimate global average intrinsic dimensionality of a data set.
EstimateIntrinsicDimensionality(DistanceFunction<? super O>, IntrinsicDimensionalityEstimator, double, double) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.EstimateIntrinsicDimensionality
Constructor.
EstimateIntrinsicDimensionality.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics
Parameterization class.
EstimateIntrinsicDimensionality.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.EstimateIntrinsicDimensionality.Parameterizer
 
estimateViewport() - Method in class de.lmu.ifi.dbs.elki.visualization.projections.AffineProjection
 
estimateViewport() - Method in interface de.lmu.ifi.dbs.elki.visualization.projections.Projection2D
Estimate the viewport requirements
estimateViewport() - Method in class de.lmu.ifi.dbs.elki.visualization.projections.Simple2D
 
estimateY(Matrix) - Method in class de.lmu.ifi.dbs.elki.math.statistics.MultipleLinearRegression
Perform an estimation of y on the specified matrix.
estimateY(double) - Method in class de.lmu.ifi.dbs.elki.math.statistics.PolynomialRegression
Performs an estimation of y on the specified x value.
estimator - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.IDOS
Estimator for intrinsic dimensionality.
estimator - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.IDOS.Parameterizer
Estimator for intrinsic dimensionality.
estimator - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.IntrinsicDimensionalityOutlier
Estimator for intrinsic dimensionality.
estimator - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.IntrinsicDimensionalityOutlier.Parameterizer
Estimator for intrinsic dimensionality.
estimator - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.EstimateIntrinsicDimensionality
Estimation method.
estimator - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.EstimateIntrinsicDimensionality.Parameterizer
Estimation method.
ESTIMATOR_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.IDOS.Parameterizer
The class used for estimating the intrinsic dimensionality.
ESTIMATOR_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic.IntrinsicDimensionalityOutlier.Parameterizer
Class to use for estimating the ID.
ESTIMATOR_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.EstimateIntrinsicDimensionality.Parameterizer
Estimation method
estimators - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseBetaNormalization
Stores the distribution estimators
estimators - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseBetaNormalization.Parameterizer
Stores the distribution estimators
estimators - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseCDFNormalization
Stores the distribution estimators
estimators - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise.AttributeWiseCDFNormalization.Parameterizer
Stores the distribution estimators
etag - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotSelectionVisualization.Instance
Element for the events
etag - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolAxisRangeVisualization.Instance
Element for the rectangle to add listeners
etag - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.parallel.selection.SelectionToolLineVisualization.Instance
Element for the rectangle to add listeners
etag - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.MoveObjectsToolVisualization.Instance
Element for the rectangle to add listeners
etag - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolCubeVisualization.Instance
Element for the rectangle to add listeners.
etag - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection.SelectionToolDotVisualization.Instance
Element for the rectangle to add listeners
EUCLIDEAN_KAPPA - Static variable in class de.lmu.ifi.dbs.elki.visualization.svg.SVGHyperSphere
Factor used for approximating circles with cubic beziers.
EuclideanDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski
Euclidean distance for NumberVectors.
EuclideanDistanceFunction() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.EuclideanDistanceFunction
Deprecated.
Use static instance!
EuclideanDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski
Parameterization class.
EuclideanDistanceFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski.EuclideanDistanceFunction.Parameterizer
 
EuclideanHashFunctionFamily - Class in de.lmu.ifi.dbs.elki.index.lsh.hashfamilies
2-stable hash function family for Euclidean distances.
EuclideanHashFunctionFamily(RandomFactory, double, int) - Constructor for class de.lmu.ifi.dbs.elki.index.lsh.hashfamilies.EuclideanHashFunctionFamily
Constructor.
EuclideanHashFunctionFamily.Parameterizer - Class in de.lmu.ifi.dbs.elki.index.lsh.hashfamilies
Parameterization class.
EuclideanHashFunctionFamily.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.index.lsh.hashfamilies.EuclideanHashFunctionFamily.Parameterizer
 
euclideanLength() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Vector
Returns the length of this vector.
euclideanLength(double[]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.VMath
Euclidean length of the vector
EuclideanRStarTreeKNNQuery<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query
Instance of a KNN query for a particular spatial index.
EuclideanRStarTreeKNNQuery(AbstractRStarTree<?, ?, ?>, Relation<? extends O>) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.EuclideanRStarTreeKNNQuery
Constructor.
EuclideanRStarTreeRangeQuery<O extends NumberVector> - Class in de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query
Instance of a range query for a particular spatial index.
EuclideanRStarTreeRangeQuery(AbstractRStarTree<?, ?, ?>, Relation<? extends O>) - Constructor for class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.EuclideanRStarTreeRangeQuery
Constructor.
EULERS_CONST - Static variable in class de.lmu.ifi.dbs.elki.math.statistics.distribution.GammaDistribution
Euler–Mascheroni constant
eval(double, double[]) - Method in interface de.lmu.ifi.dbs.elki.math.linearalgebra.fitting.FittingFunction
Compute value at position x as well as gradients for the parameters
eval(double, double[]) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.fitting.GaussianFittingFunction
compute the mixture of Gaussians at the given position
evals - Variable in class de.lmu.ifi.dbs.elki.gui.multistep.panels.EvaluationTabPanel
The data input configured
evals - Variable in class de.lmu.ifi.dbs.elki.gui.multistep.panels.OutputTabPanel
Algorithm step to run on.
evalTab - Variable in class de.lmu.ifi.dbs.elki.gui.multistep.MultiStepGUI
Evaluation panel.
evaluate(Cluster<?>, DoubleDBIDList) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.AbstractScoreEvaluation
 
evaluate(DBIDs, DoubleDBIDList) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.AbstractScoreEvaluation
 
evaluate(DBIDs, OutlierResult) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.AbstractScoreEvaluation
 
evaluate(ScoreEvaluation.Predicate<? super I>, I) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.AveragePrecisionEvaluation
 
evaluate(ScoreEvaluation.Predicate<? super I>, I) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.MaximumF1Evaluation
 
evaluate(ScoreEvaluation.Predicate<? super I>, I) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.PrecisionAtKEvaluation
 
evaluate(ScoreEvaluation.Predicate<? super I>, I) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.ROCEvaluation
 
evaluate(ScoreEvaluation.Predicate<? super I>, I) - Method in interface de.lmu.ifi.dbs.elki.evaluation.scores.ScoreEvaluation
Evaluate a given predicate and iterator.
evaluate(Cluster<?>, DoubleDBIDList) - Method in interface de.lmu.ifi.dbs.elki.evaluation.scores.ScoreEvaluation
Evaluate given a cluster (of positive elements) and a scoring list.
evaluate(DBIDs, DoubleDBIDList) - Method in interface de.lmu.ifi.dbs.elki.evaluation.scores.ScoreEvaluation
Evaluate given a list of positives and a scoring.
evaluate(DBIDs, OutlierResult) - Method in interface de.lmu.ifi.dbs.elki.evaluation.scores.ScoreEvaluation
Evaluate given a set of positives and a scoring.
EvaluateCIndex<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Compute the C-index of a data set.
EvaluateCIndex(DistanceFunction<? super O>, NoiseHandling) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateCIndex
Constructor.
EvaluateCIndex.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Parameterization class.
EvaluateCIndex.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateCIndex.Parameterizer
 
EvaluateClustering - Class in de.lmu.ifi.dbs.elki.evaluation.clustering
Evaluate a clustering result by comparing it to an existing cluster label.
EvaluateClustering(ClusteringAlgorithm<?>, boolean, boolean) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.EvaluateClustering
Constructor.
evaluateClustering(Database, Relation<? extends O>, DistanceQuery<O>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateCIndex
Evaluate a single clustering.
evaluateClustering(Database, Relation<? extends NumberVector>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs
Evaluate a single clustering.
evaluateClustering(Database, Relation<? extends NumberVector>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateDaviesBouldin
Evaluate a single clustering.
evaluateClustering(Database, Relation<? extends NumberVector>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluatePBMIndex
Evaluate a single clustering.
evaluateClustering(Database, Relation<O>, DistanceQuery<O>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSilhouette
Evaluate a single clustering.
evaluateClustering(Database, Relation<? extends NumberVector>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSimplifiedSilhouette
Evaluate a single clustering.
evaluateClustering(Database, Relation<? extends NumberVector>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSquaredErrors
Evaluate a single clustering.
evaluateClustering(Database, Relation<? extends NumberVector>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateVarianceRatioCriteria
Evaluate a single clustering.
EvaluateClustering.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.clustering
Parameterization class.
EvaluateClustering.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.EvaluateClustering.Parameterizer
 
EvaluateClustering.ScoreResult - Class in de.lmu.ifi.dbs.elki.evaluation.clustering
Result object for outlier score judgements.
EvaluateClustering.ScoreResult(ClusterContingencyTable) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.EvaluateClustering.ScoreResult
Constructor.
evaluateClusters(ArrayList<PROCLUS<V>.PROCLUSCluster>, long[][], Relation<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS
Evaluates the quality of the clusters.
EvaluateConcordantPairs<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Compute the Gamma Criterion of a data set.
EvaluateConcordantPairs(PrimitiveDistanceFunction<? super NumberVector>, NoiseHandling) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs
Constructor.
EvaluateConcordantPairs.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Parameterization class.
EvaluateConcordantPairs.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateConcordantPairs.Parameterizer
 
EvaluateDaviesBouldin - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Compute the Davies-Bouldin index of a data set.
EvaluateDaviesBouldin(NumberVectorDistanceFunction<?>, NoiseHandling) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateDaviesBouldin
Constructor.
EvaluateDaviesBouldin.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Parameterization class.
EvaluateDaviesBouldin.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateDaviesBouldin.Parameterizer
 
EvaluateIntrinsicDimensionalityEstimators - Class in de.lmu.ifi.dbs.elki.application.experiments
Class for testing the estimation quality of intrinsic dimensionality estimators.
EvaluateIntrinsicDimensionalityEstimators(int, int, int, int, EvaluateIntrinsicDimensionalityEstimators.Aggregate, EvaluateIntrinsicDimensionalityEstimators.OutputFormat, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators
Constructor.
EvaluateIntrinsicDimensionalityEstimators.Aggregate - Enum in de.lmu.ifi.dbs.elki.application.experiments
Aggregation methods.
EvaluateIntrinsicDimensionalityEstimators.Aggregate() - Constructor for enum de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Aggregate
 
EvaluateIntrinsicDimensionalityEstimators.OutputFormat - Enum in de.lmu.ifi.dbs.elki.application.experiments
Output format
EvaluateIntrinsicDimensionalityEstimators.OutputFormat() - Constructor for enum de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.OutputFormat
 
EvaluateIntrinsicDimensionalityEstimators.Parameterizer - Class in de.lmu.ifi.dbs.elki.application.experiments
Parameterization class.
EvaluateIntrinsicDimensionalityEstimators.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.application.experiments.EvaluateIntrinsicDimensionalityEstimators.Parameterizer
 
evaluateKNN(double[], ModifiableDoubleDBIDList, Relation<?>, TObjectIntHashMap<Object>, Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRetrievalPerformance.KNNEvaluator
Evaluate by simulating kNN classification for k=1...maxk
evaluateOrderingResult(int, SetDBIDs, DBIDs) - Method in class de.lmu.ifi.dbs.elki.evaluation.outlier.OutlierRankingEvaluation
 
evaluateOutlierResult(Database, OutlierResult) - Method in class de.lmu.ifi.dbs.elki.evaluation.histogram.ComputeOutlierHistogram
Evaluate a single outlier result as histogram.
evaluateOutlierResult(int, SetDBIDs, OutlierResult) - Method in class de.lmu.ifi.dbs.elki.evaluation.outlier.OutlierRankingEvaluation
 
EvaluatePBMIndex - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Compute the PBM of a data set Reference: M.
EvaluatePBMIndex(NumberVectorDistanceFunction<?>, NoiseHandling) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluatePBMIndex
Constructor.
EvaluatePBMIndex.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Parameterization class.
EvaluatePBMIndex.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluatePBMIndex.Parameterizer
 
EvaluatePrecomputedOutlierScores - Class in de.lmu.ifi.dbs.elki.application.greedyensemble
Class to load an outlier detection summary file, as produced by ComputeKNNOutlierScores, and compute popular evaluation metrics for it.
EvaluatePrecomputedOutlierScores(InputStep, Pattern, File, String) - Constructor for class de.lmu.ifi.dbs.elki.application.greedyensemble.EvaluatePrecomputedOutlierScores
Constructor.
EvaluatePrecomputedOutlierScores.Parameterizer - Class in de.lmu.ifi.dbs.elki.application.greedyensemble
Parameterization class.
EvaluatePrecomputedOutlierScores.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.application.greedyensemble.EvaluatePrecomputedOutlierScores.Parameterizer
 
EvaluateRankingQuality<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics
Evaluate a distance function with respect to kNN queries.
EvaluateRankingQuality(DistanceFunction<? super V>, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRankingQuality
Constructor.
EvaluateRankingQuality.Parameterizer<V extends NumberVector> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics
Parameterization class.
EvaluateRankingQuality.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRankingQuality.Parameterizer
 
EvaluateRetrievalPerformance<O> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics
Evaluate a distance functions performance by computing the mean average precision, ROC, and NN classification performance when ranking the objects by distance.
EvaluateRetrievalPerformance(DistanceFunction<? super O>, double, RandomFactory, boolean, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRetrievalPerformance
Constructor.
EvaluateRetrievalPerformance.KNNEvaluator - Class in de.lmu.ifi.dbs.elki.algorithm.statistics
Evaluate kNN retrieval performance.
EvaluateRetrievalPerformance.KNNEvaluator() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRetrievalPerformance.KNNEvaluator
 
EvaluateRetrievalPerformance.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics
Parameterization class.
EvaluateRetrievalPerformance.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRetrievalPerformance.Parameterizer
 
EvaluateRetrievalPerformance.RetrievalPerformanceResult - Class in de.lmu.ifi.dbs.elki.algorithm.statistics
Result object for MAP scores.
EvaluateRetrievalPerformance.RetrievalPerformanceResult(int, double, double, double[]) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRetrievalPerformance.RetrievalPerformanceResult
Constructor.
EvaluateSilhouette<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Compute the silhouette of a data set.
EvaluateSilhouette(DistanceFunction<? super O>, NoiseHandling, boolean) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSilhouette
Constructor.
EvaluateSilhouette(DistanceFunction<? super O>, boolean) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSilhouette
Constructor.
EvaluateSilhouette.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Parameterization class.
EvaluateSilhouette.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSilhouette.Parameterizer
 
EvaluateSimplifiedSilhouette - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Compute the simplified silhouette of a data set.
EvaluateSimplifiedSilhouette(NumberVectorDistanceFunction<?>, NoiseHandling, boolean) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSimplifiedSilhouette
Constructor.
EvaluateSimplifiedSilhouette.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Parameterization class.
EvaluateSimplifiedSilhouette.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSimplifiedSilhouette.Parameterizer
 
EvaluateSquaredErrors - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Evaluate a clustering by reporting the squared errors (SSE, SSQ), as used by k-means.
EvaluateSquaredErrors(NumberVectorDistanceFunction<?>, NoiseHandling) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSquaredErrors
Constructor.
EvaluateSquaredErrors.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Parameterization class.
EvaluateSquaredErrors.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateSquaredErrors.Parameterizer
 
EvaluateVarianceRatioCriteria<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Compute the Variance Ratio Criteria of a data set.
EvaluateVarianceRatioCriteria(NoiseHandling, boolean) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateVarianceRatioCriteria
Constructor.
EvaluateVarianceRatioCriteria.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.internal
Parameterization class.
EvaluateVarianceRatioCriteria.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateVarianceRatioCriteria.Parameterizer
 
evaluationName - Variable in class de.lmu.ifi.dbs.elki.evaluation.classification.ConfusionMatrixEvaluationResult
Holds the used EvaluationProcedure.
EvaluationResult - Class in de.lmu.ifi.dbs.elki.result
Abstract evaluation result.
EvaluationResult(String, String) - Constructor for class de.lmu.ifi.dbs.elki.result.EvaluationResult
Constructor.
EvaluationResult.Measurement - Class in de.lmu.ifi.dbs.elki.result
Class representing a single measurement.
EvaluationResult.Measurement(String, double, double, double, boolean) - Constructor for class de.lmu.ifi.dbs.elki.result.EvaluationResult.Measurement
Constructor.
EvaluationResult.Measurement(String, double, double, double, double, boolean) - Constructor for class de.lmu.ifi.dbs.elki.result.EvaluationResult.Measurement
Constructor.
EvaluationResult.MeasurementGroup - Class in de.lmu.ifi.dbs.elki.result
A group of evaluation measurements.
EvaluationResult.MeasurementGroup(String) - Constructor for class de.lmu.ifi.dbs.elki.result.EvaluationResult.MeasurementGroup
Constructor.
evaluationStep - Variable in class de.lmu.ifi.dbs.elki.KDDTask
The evaluation step.
evaluationStep - Variable in class de.lmu.ifi.dbs.elki.KDDTask.Parameterizer
 
EvaluationStep - Class in de.lmu.ifi.dbs.elki.workflow
The "evaluation" step, where data is analyzed.
EvaluationStep(List<Evaluator>) - Constructor for class de.lmu.ifi.dbs.elki.workflow.EvaluationStep
Constructor.
EvaluationStep.Evaluation - Class in de.lmu.ifi.dbs.elki.workflow
Class to handle running the evaluators on a database instance.
EvaluationStep.Evaluation(ResultHierarchy, List<Evaluator>) - Constructor for class de.lmu.ifi.dbs.elki.workflow.EvaluationStep.Evaluation
Constructor.
EvaluationStep.Parameterizer - Class in de.lmu.ifi.dbs.elki.workflow
Parameterization class.
EvaluationStep.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.workflow.EvaluationStep.Parameterizer
 
EvaluationTabPanel - Class in de.lmu.ifi.dbs.elki.gui.multistep.panels
Panel to handle result evaluation
EvaluationTabPanel(InputTabPanel, AlgorithmTabPanel) - Constructor for class de.lmu.ifi.dbs.elki.gui.multistep.panels.EvaluationTabPanel
Constructor.
EvaluationVisualization - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj
Pseudo-Visualizer, that lists the cluster evaluation results found.
EvaluationVisualization() - Constructor for class de.lmu.ifi.dbs.elki.visualization.visualizers.visunproj.EvaluationVisualization
Constructor.
Evaluator - Interface in de.lmu.ifi.dbs.elki.evaluation
Interface for post-algorithm evaluations, such as histograms, outlier score evaluations, ...
EVALUATOR_ID - Static variable in class de.lmu.ifi.dbs.elki.workflow.EvaluationStep.Parameterizer
Parameter ID to specify the evaluators to run.
evaluators - Variable in class de.lmu.ifi.dbs.elki.workflow.EvaluationStep.Evaluation
Evaluators to run.
evaluators - Variable in class de.lmu.ifi.dbs.elki.workflow.EvaluationStep
Evaluators to run.
evaluators - Variable in class de.lmu.ifi.dbs.elki.workflow.EvaluationStep.Parameterizer
Evaluators to run
evaluteResult(Database, Clustering<?>, Clustering<?>) - Method in class de.lmu.ifi.dbs.elki.evaluation.clustering.EvaluateClustering
Evaluate a clustering result.
eventarea - Variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.optics.OPTICSPlotCutVisualization.Instance
Sensitive (clickable) area
eventManager - Variable in class de.lmu.ifi.dbs.elki.database.AbstractDatabase
The event manager, collects events and fires them on demand.
EVT_DBLCLICK_DELAY - Static variable in class de.lmu.ifi.dbs.elki.visualization.visualizers.pairsegments.CircleSegmentsVisualizer.Instance.SegmentListenerProxy
Mouse double click time window in milliseconds TODO: does Batik have double click events?
exact - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceStatisticsWithClasses
Compute exactly (slower).
exact - Variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceStatisticsWithClasses.Parameterizer
Exactness flag.
EXACT_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceStatisticsWithClasses.Parameterizer
Flag to compute exact value range for binning.
exactMinMax(Relation<O>, DistanceQuery<O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.statistics.DistanceStatisticsWithClasses
Compute the exact maximum and minimum.
exception(CharSequence, Throwable) - Method in class de.lmu.ifi.dbs.elki.logging.Logging
Log a message with exception at the 'severe' level.
exception(Throwable) - Method in class de.lmu.ifi.dbs.elki.logging.Logging
Log an exception at the 'severe' level.
exception(Throwable) - Static method in class de.lmu.ifi.dbs.elki.logging.LoggingUtil
Static version to log a severe exception.
exception(String, Throwable) - Static method in class de.lmu.ifi.dbs.elki.logging.LoggingUtil
Static version to log a severe exception.
ExceptionMessages - Interface in de.lmu.ifi.dbs.elki.utilities.exceptions
Interface to collect exception messages that are used in several cases.
excessOfMass() - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction.TempCluster
Excess of mass measure.
excludeNotCovered(ModifiableDoubleDBIDList, double, ModifiableDoubleDBIDList) - Method in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree
Retain all elements within the current cover.
execute() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.ParameterTabPanel
Execute the task.
executed - Variable in class de.lmu.ifi.dbs.elki.gui.multistep.panels.InputTabPanel
Signal when an database input has been executed.
executeResize(double) - Method in class de.lmu.ifi.dbs.elki.visualization.batikutil.LazyCanvasResizer
Callback function that needs to be overridden with actual implementations.
executeStep() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.AlgorithmTabPanel
 
executeStep() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.EvaluationTabPanel
 
executeStep() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.InputTabPanel
 
executeStep() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.LoggingTabPanel
 
executeStep() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.OutputTabPanel
 
executeStep() - Method in class de.lmu.ifi.dbs.elki.gui.multistep.panels.ParameterTabPanel
Execute the configured step.
Executor - Interface in de.lmu.ifi.dbs.elki.parallel
Processor executor.
executor - Variable in class de.lmu.ifi.dbs.elki.parallel.ParallelCore
Executor service.
existed - Variable in class de.lmu.ifi.dbs.elki.persistent.OnDiskArrayPageFile
Whether or not the file originally existed
existed - Variable in class de.lmu.ifi.dbs.elki.persistent.PersistentPageFile
Whether we are initializing from an existing file.
existing - Variable in class de.lmu.ifi.dbs.elki.data.ClassLabel.Factory
Set for reusing the same objects.
existing - Variable in class de.lmu.ifi.dbs.elki.database.relation.ConvertToStringView
The database we use
exp - Variable in class de.lmu.ifi.dbs.elki.result.EvaluationResult.Measurement
Observed value, minimum, maximum, expected value.
expandCluster(Relation<O>, RangeQuery<O>, DBIDRef, FiniteProgress, IndefiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN
DBSCAN-function expandCluster.
expandCluster(DBIDRef, int, WritableIntegerDataStore, T, ArrayModifiableDBIDs, FiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Instance
Set-based expand cluster implementation.
expandCluster(int, WritableIntegerDataStore, KNNQuery<O>, DBIDs, double, FiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.LSDBC
Set-based expand cluster implementation.
expandCluster(SimilarityQuery<O>, DBIDRef, FiniteProgress, IndefiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.SNNClustering
DBSCAN-function expandCluster adapted to SNN criterion.
expandClusterOrder(DBID, ClusterOrder, DistanceQuery<V>, FiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.FastOPTICS
OPTICS algorithm for processing a point, but with different density estimates
expandClusterOrder(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSHeap.Instance
OPTICS-function expandClusterOrder.
expandClusterOrder(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSList.Instance
OPTICS-function expandClusterOrder.
expandDBID(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.HiCO.Instance
 
expandDBID(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.GeneralizedOPTICS.Instance
Add the current DBID to the cluster order, and expand its neighbors if minPts and similar conditions are satisfied.
expandDBID(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH.Instance
 
expandDBID(DBIDRef) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.HiSC.Instance
 
expandDirNodes(SpatialPrimitiveDistanceFunction<NV>, DeLiCluNode, DeLiCluNode) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.DeLiClu
Expands the specified directory nodes.
expanded - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTree
Holds the ids of the expanded nodes.
expandLeafNodes(SpatialPrimitiveDistanceFunction<NV>, DeLiCluNode, DeLiCluNode, DataStore<KNNList>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.DeLiClu
Expands the specified leaf nodes.
expandNode(O, KNNHeap, ComparableMinHeap<DoubleDistanceSearchCandidate>, double, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.EuclideanRStarTreeKNNQuery
 
expandNode(O, KNNHeap, ComparableMinHeap<DoubleDistanceSearchCandidate>, double, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.RStarTreeKNNQuery
 
expandNodes(DeLiCluTree, SpatialPrimitiveDistanceFunction<NV>, DeLiClu<NV>.SpatialObjectPair, DataStore<KNNList>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.DeLiClu
Expands the spatial nodes of the specified pair.
expansion - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree
Constant expansion rate. 2 would be the intuitive value, but the original version used 1.3, so we copy this.
expansion - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree.Factory
Constant expansion rate. 2 would be the intuitive value, but the original version used 1.3, so we copy this.
expansion - Variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree.Factory.Parameterizer
Expansion rate.
EXPANSION_ID - Static variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.covertree.AbstractCoverTree.Factory.Parameterizer
Expansion rate of the tree (going upward).
expect - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.COP
Expected amount of outliers.
expect - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.COP.Parameterizer
Expected amount of outliers.
expect - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.trivial.TrivialGeneratedOutlier
Expected share of outliers.
expect - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.trivial.TrivialGeneratedOutlier.Parameterizer
Expected share of outliers
EXPECT_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.COP.Parameterizer
Expected share of outliers.
EXPECT_ID - Static variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.trivial.TrivialGeneratedOutlier.Parameterizer
Expected share of outliers
expected(int, int) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.AveragePrecisionEvaluation
 
expected(int, int) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.MaximumF1Evaluation
 
expected(int, int) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.PrecisionAtKEvaluation
 
expected(int, int) - Method in class de.lmu.ifi.dbs.elki.evaluation.scores.ROCEvaluation
 
expected(int, int) - Method in interface de.lmu.ifi.dbs.elki.evaluation.scores.ScoreEvaluation
Expected score for a random result.
expirePage(P) - Method in class de.lmu.ifi.dbs.elki.persistent.LRUCache
Write page through to disk.
explain - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredAutotuningRunner.Cand
Score
explainedVariance - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredResult
The amount of Variance explained by strong Eigenvalues
ExpMADDistributionEstimator<D extends Distribution> - Interface in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
Distribuition estimators that use the method of moments (MOM) in exponentiated data.
EXPONENT_OVERFLOW - Static variable in class de.lmu.ifi.dbs.elki.utilities.FormatUtil
Preallocated exceptions.
ExponentialDistribution - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution
Exponential distribution.
ExponentialDistribution(double) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution
Constructor.
ExponentialDistribution(double, double) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution
Constructor.
ExponentialDistribution(double, Random) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution
Constructor.
ExponentialDistribution(double, double, Random) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution
Constructor.
ExponentialDistribution(double, double, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution
Constructor.
ExponentialDistribution.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution
Parameterization class
ExponentialDistribution.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution.Parameterizer
 
ExponentialLMMEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
Estimate the parameters of a Gamma Distribution, using the methods of L-Moments (LMM).
ExponentialLMMEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialLMMEstimator
Constructor.
ExponentialLMMEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
Parameterization class.
ExponentialLMMEstimator.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialLMMEstimator.Parameterizer
 
ExponentiallyModifiedGaussianDistribution - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution
Exponentially modified Gaussian (EMG) distribution (ExGaussian distribution) is a combination of a normal distribution and an exponential distribution.
ExponentiallyModifiedGaussianDistribution(double, double, double, Random) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentiallyModifiedGaussianDistribution
Constructor for ExGaussian distribution
ExponentiallyModifiedGaussianDistribution(double, double, double, RandomFactory) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentiallyModifiedGaussianDistribution
Constructor for ExGaussian distribution
ExponentiallyModifiedGaussianDistribution(double, double, double) - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentiallyModifiedGaussianDistribution
Constructor for ExGaussian distribution
ExponentiallyModifiedGaussianDistribution.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution
Parameterization class
ExponentiallyModifiedGaussianDistribution.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentiallyModifiedGaussianDistribution.Parameterizer
 
ExponentialMADEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
Estimate Exponential distribution parameters using Median and MAD.
ExponentialMADEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMADEstimator
Private constructor, use static instance!
ExponentialMADEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
Parameterization class.
ExponentialMADEstimator.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMADEstimator.Parameterizer
 
ExponentialMedianEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
Estimate Exponential distribution parameters using Median and MAD.
ExponentialMedianEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMedianEstimator
Private constructor, use static instance!
ExponentialMedianEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
Parameterization class.
ExponentialMedianEstimator.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMedianEstimator.Parameterizer
 
ExponentialMOMEstimator - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
Estimate Exponential distribution parameters using the mean, which is the maximum-likelihood estimate (MLE), but not very robust.
ExponentialMOMEstimator() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMOMEstimator
Private constructor, use static instance!
ExponentialMOMEstimator.Parameterizer - Class in de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator
Parameterization class.
ExponentialMOMEstimator.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator.ExponentialMOMEstimator.Parameterizer
 
ExponentialStddevWeight - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions
Exponential Weight function, scaled such that the result it 0.1 at distance == max stddev * exp(-.5 * distance/stddev) This is similar to the Gaussian weight function, except distance/stddev is not squared.
ExponentialStddevWeight() - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions.ExponentialStddevWeight
 
ExponentialWeight - Class in de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions
Exponential Weight function, scaled such that the result it 0.1 at distance == max exp(-2.3025850929940455 * distance/max) This is similar to the Gaussian weight function, except distance/max is not squared
ExponentialWeight() - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions.ExponentialWeight
 
exportItem - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.ResultWindow.DynamicMenu
The "Export" button, to save the image
ExportVisualizations - Class in de.lmu.ifi.dbs.elki.visualization
Class that automatically generates all visualizations and exports them into SVG files.
ExportVisualizations(File, VisualizerParameterizer, double) - Constructor for class de.lmu.ifi.dbs.elki.visualization.ExportVisualizations
Constructor.
ExportVisualizations.Parameterizer - Class in de.lmu.ifi.dbs.elki.visualization
Parameterization class
ExportVisualizations.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.visualization.ExportVisualizations.Parameterizer
 
extend(SpatialComparable) - Method in class de.lmu.ifi.dbs.elki.data.ModifiableHyperBoundingBox
Extend the bounding box by some other spatial object.
extend(A, ArrayAdapter<T, A>, T) - Static method in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ExtendedArray
Static wrapper that has a nicer generics signature.
ExtendedArray<T> - Class in de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike
Class to extend an array with a single element virtually.
ExtendedArray(Object, ArrayAdapter<T, Object>, T) - Constructor for class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ExtendedArray
Constructor.
ExtendedNeighborhood - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood
Neighborhood obtained by computing the k-fold closure of an existing neighborhood.
ExtendedNeighborhood(DataStore<DBIDs>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExtendedNeighborhood
Constructor.
ExtendedNeighborhood.Factory<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood
Factory class.
ExtendedNeighborhood.Factory(NeighborSetPredicate.Factory<O>, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExtendedNeighborhood.Factory
Constructor.
ExtendedNeighborhood.Factory.Parameterizer<O> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood
Parameterization class.
ExtendedNeighborhood.Factory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExtendedNeighborhood.Factory.Parameterizer
 
extendMBR(SpatialComparable) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.SpatialDirectoryEntry
Extend the MBR of this node.
extendNeighborhood(Database, Relation<? extends O>) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExtendedNeighborhood.Factory
Method to load the external neighbors.
EXTENSION - Static variable in class de.lmu.ifi.dbs.elki.result.textwriter.MultipleFilesOutput
File name extension.
ExternalClustering - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.meta
Read an external clustering result from a file, such as produced by ClusteringVectorDumper.
ExternalClustering(File) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.meta.ExternalClustering
Constructor.
ExternalClustering.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.meta
Parameterization class
ExternalClustering.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.meta.ExternalClustering.Parameterizer
 
ExternalDoubleOutlierScore - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.meta
External outlier detection scores, loading outlier scores from an external file.
ExternalDoubleOutlierScore(File, Pattern, Pattern, boolean, ScalingFunction) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.ExternalDoubleOutlierScore
Constructor.
ExternalDoubleOutlierScore.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.meta
Parameterization class
ExternalDoubleOutlierScore.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.meta.ExternalDoubleOutlierScore.Parameterizer
 
ExternalID - Class in de.lmu.ifi.dbs.elki.data
External ID objects.
ExternalID(String) - Constructor for class de.lmu.ifi.dbs.elki.data.ExternalID
Constructor.
EXTERNALID - Static variable in class de.lmu.ifi.dbs.elki.data.type.TypeUtil
External ID type.
EXTERNALID_INDEX_ID - Static variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ExternalIDFilter.Parameterizer
Parameter that specifies the index of the label to be used as external Id, starting at 0.
ExternalIDFilter - Class in de.lmu.ifi.dbs.elki.datasource.filter.typeconversions
Class that turns a label column into an external ID column.
ExternalIDFilter(int) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ExternalIDFilter
Constructor.
ExternalIDFilter.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource.filter.typeconversions
Parameterization class.
ExternalIDFilter.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ExternalIDFilter.Parameterizer
 
externalIdIndex - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ExternalIDFilter
The index of the label to be used as external Id.
externalIdIndex - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.typeconversions.ExternalIDFilter.Parameterizer
 
ExternalIDJoinDatabaseConnection - Class in de.lmu.ifi.dbs.elki.datasource
Joins multiple data sources by their label
ExternalIDJoinDatabaseConnection(List<ObjectFilter>, List<DatabaseConnection>) - Constructor for class de.lmu.ifi.dbs.elki.datasource.ExternalIDJoinDatabaseConnection
Constructor.
ExternalIDJoinDatabaseConnection.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource
Parameterization class.
ExternalIDJoinDatabaseConnection.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.datasource.ExternalIDJoinDatabaseConnection.Parameterizer
 
ExternalizablePage - Interface in de.lmu.ifi.dbs.elki.persistent
Base interface for externalizable pages.
ExternalNeighborhood - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood
A precomputed neighborhood, loaded from an external file.
ExternalNeighborhood(DataStore<DBIDs>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExternalNeighborhood
Constructor.
ExternalNeighborhood.Factory - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood
Factory class.
ExternalNeighborhood.Factory(File) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExternalNeighborhood.Factory
Constructor.
ExternalNeighborhood.Factory.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood
Parameterization class.
ExternalNeighborhood.Factory.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.ExternalNeighborhood.Factory.Parameterizer
 
extra - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike.ExtendedArray
The extra element
extra - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.ItrAnc
Additional object to return as first result.
extra - Variable in class de.lmu.ifi.dbs.elki.utilities.datastructures.hierarchy.HashMapHierarchy.ItrDesc
Additional object to return as first result.
EXTRA_INTEGRITY_CHECKS - Static variable in class de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree
Debugging flag: do extra integrity checks.
EXTRA_INTEGRITY_CHECKS - Static variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.AbstractRStarTree
Development flag: This will enable some extra integrity checks on the tree.
extract(int, int, int, boolean, FPGrowth.FPTree.Collector) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPTree
Extract itemsets ending in the given item.
extract(int, int, int, int, int[], int, int[], int[], boolean, FPGrowth.FPTree.Collector) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPTree
Extract itemsets ending in the given item.
extractClusters(DBIDs, DBIDDataStore, DoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ExtractFlatClusteringFromHierarchy
Extract all clusters from the pi-lambda-representation.
extractClusters(DBIDs, DBIDDataStore, DoubleDataStore, DoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.HDBSCANHierarchyExtraction
Extract all clusters from the pi-lambda-representation.
extractClusters(DBIDs, DBIDDataStore, DoubleDataStore, DoubleDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction
Extract all clusters from the pi-lambda-representation.
extractClusters(ClusterOrder, Relation<?>, double, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.optics.OPTICSXi
Extract clusters from a cluster order result.
extractClusters(Relation<V>, DiSH.DiSHClusterOrder) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH
Extracts the clusters from the cluster order.
extractCorrelationClusters(Clustering<Model>, Relation<V>, int, ERiCNeighborPredicate<V>.Instance) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ERiC
Extracts the correlation clusters and noise from the copac result and returns a mapping of correlation dimension to maps of clusters within this correlation dimension.
ExtractFlatClusteringFromHierarchy - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction
Extract a flat clustering from a full hierarchy, represented in pointer form.
ExtractFlatClusteringFromHierarchy(HierarchicalClusteringAlgorithm, int, boolean, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ExtractFlatClusteringFromHierarchy
Constructor.
ExtractFlatClusteringFromHierarchy(HierarchicalClusteringAlgorithm, double, boolean, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ExtractFlatClusteringFromHierarchy
Constructor.
ExtractFlatClusteringFromHierarchy.Parameterizer - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction
Parameterization class.
ExtractFlatClusteringFromHierarchy.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ExtractFlatClusteringFromHierarchy.Parameterizer
 
ExtractFlatClusteringFromHierarchy.ThresholdMode - Enum in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction
Threshold mode.
ExtractFlatClusteringFromHierarchy.ThresholdMode() - Constructor for enum de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.ExtractFlatClusteringFromHierarchy.ThresholdMode
 
ExtractFlatClusteringFromHierarchyEvaluator - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.extractor
Extract clusters from a hierarchical clustering, during the evaluation phase.
ExtractFlatClusteringFromHierarchyEvaluator(ExtractFlatClusteringFromHierarchy) - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.extractor.ExtractFlatClusteringFromHierarchyEvaluator
Constructor.
ExtractFlatClusteringFromHierarchyEvaluator.DummyHierarchicalClusteringAlgorithm - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.extractor
Dummy instance.
ExtractFlatClusteringFromHierarchyEvaluator.DummyHierarchicalClusteringAlgorithm() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.extractor.ExtractFlatClusteringFromHierarchyEvaluator.DummyHierarchicalClusteringAlgorithm
Constructor.
ExtractFlatClusteringFromHierarchyEvaluator.Parameterizer - Class in de.lmu.ifi.dbs.elki.evaluation.clustering.extractor
Parameterization class.
ExtractFlatClusteringFromHierarchyEvaluator.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.evaluation.clustering.extractor.ExtractFlatClusteringFromHierarchyEvaluator.Parameterizer
 
extractItemsets(DBIDs[], int, int, List<Itemset>) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.Eclat
 
extractItemsets(DBIDs, DBIDs[], int[], int, int, int, List<Itemset>) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.Eclat
 
extractLinear(int, int, int, int, int, int[], int, int[], FPGrowth.FPTree.Collector) - Method in class de.lmu.ifi.dbs.elki.algorithm.itemsetmining.FPGrowth.FPTree
Extract itemsets from a linear tree.
extremum_alpha_n(int, double[]) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.ParameterizationFunction
Determines the value for alpha_n where this function has a (local) extremum.
extremumType - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.ParameterizationFunction
Holds the type of the global extremum.
extremumType(int, double[], HyperBoundingBox) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash.ParameterizationFunction
Returns the type of the extremum at the specified alpha values.
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ELKI Version 0.7.0

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