E-Index (ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures)

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.
ecurr - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.OPTICSXi.SteepScanPosition: Current entry
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_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: 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: Provides the Edit Distance on Real Sequence distance for FeatureVectors.
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
EigenPair - Class in de.lmu.ifi.dbs.elki.math.linearalgebra: Helper class which encapsulates an eigenvector and its corresponding eigenvalue.
EigenPair(Vector, double) - Constructor for class de.lmu.ifi.dbs.elki.math.linearalgebra.EigenPair: Creates a new EigenPair object.
EIGENPAIR_FILTER_ABSOLUTE - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.LimitEigenPairFilter: "absolute" Flag
EIGENPAIR_FILTER_COMPOSITE_LIST - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.CompositeEigenPairFilter: The list of filters to use.
EIGENPAIR_FILTER_DELTA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.LimitEigenPairFilter: Parameter delta
EIGENPAIR_FILTER_N - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.FirstNEigenPairFilter: Paremeter n
EIGENPAIR_FILTER_PALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.ProgressiveEigenPairFilter: Parameter progressive alpha.
EIGENPAIR_FILTER_RALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.RelativeEigenPairFilter: Parameter relative alpha.
EIGENPAIR_FILTER_WALPHA - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.WeakEigenPairFilter: OptionID for the weak alpha value of WeakEigenPairFilter, ProgressiveEigenPairFilter and SignificantEigenPairFilter
EigenPairFilter - Interface in de.lmu.ifi.dbs.elki.math.linearalgebra.pca: The eigenpair filter is used to filter eigenpairs (i.e. eigenvectors and their corresponding eigenvalues) which are a result of a Variance Analysis Algorithm, e.g.
eigenPairFilter - Variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredRunner: Holds the instance of the EigenPairFilter specified by PCAFilteredRunner.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.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.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.
elementsAtRadius(List<DoubleIntPair>, double) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.lof.LOCI: Get the number of objects for a given radius, from the list of critical distances, storing (radius, count) pairs.
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(Class<?>, ClassLoader) - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceLoader: Constructor.
ELKIServiceLoader(Class<?>) - Constructor for class de.lmu.ifi.dbs.elki.utilities.ELKIServiceLoader: Constructor, using the system class loader.
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<?>> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering: Provides the EM algorithm (clustering by expectation maximization).
EM(int, double, KMeansInitialization<V>, int, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.EM: Constructor.
em - Variable in class de.lmu.ifi.dbs.elki.algorithm.outlier.EMOutlier.Parameterizer
EM.Parameterizer<V extends NumberVector<?>> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering: Parameterization class.
EM.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.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.EMOutlier: Inner algorithm.
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<NV extends NumberVector<?>> - Class in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster: Instance.
EMClusterVisualization.Instance(VisualizationTask) - 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<V extends FeatureVector<?>> - Class in de.lmu.ifi.dbs.elki.data.model: Cluster model of an EM cluster, providing a mean and a full covariance Matrix.
EMModel(V, Matrix) - Constructor for class de.lmu.ifi.dbs.elki.data.model.EMModel: Constructor.
EMOutlier<V extends NumberVector<?>> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier: outlier detection algorithm using EM Clustering.
EMOutlier(EM<V>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.EMOutlier: Constructor with an existing em clustering algorithm.
EMOutlier.Parameterizer<V extends NumberVector<?>> - Class in de.lmu.ifi.dbs.elki.algorithm.outlier: Parameterization class.
EMOutlier.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.outlier.EMOutlier.Parameterizer
EMPTY - Static variable in class de.lmu.ifi.dbs.elki.datasource.parser.ArffParser: Empty line pattern.
EMPTY_DISTS - Static variable in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleDistanceIntegerDBIDList: 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.DoubleDistanceIntegerDBIDList: Empty.
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.
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
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
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: Parameter to enable visualizers Key: -vis.enable Default: ELKI core
enableVisualizers - Variable in class de.lmu.ifi.dbs.elki.visualization.VisualizerParameterizer.Parameterizer
encodeBase64(byte[]) - Static method in class de.lmu.ifi.dbs.elki.utilities.Base64: Encode a string as Base64.
encoder - Variable in class de.lmu.ifi.dbs.elki.persistent.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.datasource.parser.Tokenizer: Current positions of result and iterator.
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
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.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.
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, adhering to Parameterizable
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, adhering to Parameterizable
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, adhering to Parameterizable
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(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(int) - Method in class de.lmu.ifi.dbs.elki.database.ids.generic.GenericDistanceDBIDList
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.metrical.mtreevariants.strategies.split.DistanceEntry: The entry of the Index.
entry - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.DoubleDistanceRStarTreeKNNQuery.DoubleDistanceEntry: Referenced entry
entry - Variable in class de.lmu.ifi.dbs.elki.index.tree.TreeIndexPathComponent: The entry of this component.
entry1 - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.DeLiClu.SpatialObjectPair: The first entry of this pair.
entry2 - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.DeLiClu.SpatialObjectPair: The second entry of this pair.
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.AbstractProjectedDBSCAN: Holds the value of AbstractProjectedDBSCAN.EPSILON_ID.
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.AbstractProjectedDBSCAN.Parameterizer
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
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: Hold the value of OPTICS.EPSILON_ID.
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.OPTICS.Parameterizer
epsilon - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.SNNClustering: Holds the value of SNNClustering.EPSILON_ID.
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.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.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.distance.distancefunction.subspace.AbstractPreferenceVectorBasedCorrelationDistanceFunction: Holds the value of AbstractPreferenceVectorBasedCorrelationDistanceFunction.EPSILON_ID.
epsilon - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.AbstractPreferenceVectorBasedCorrelationDistanceFunction.Instance: The epsilon value
epsilon - Variable in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.AbstractPreferenceVectorBasedCorrelationDistanceFunction.Parameterizer
epsilon - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.localpca.RangeQueryFilteredPCAIndex: Query epsilon.
epsilon - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.localpca.RangeQueryFilteredPCAIndex.Factory: Holds the value of RangeQueryFilteredPCAIndex.Factory.EPSILON_ID.
epsilon - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.localpca.RangeQueryFilteredPCAIndex.Factory.Parameterizer
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.index.preprocessed.subspaceproj.AbstractSubspaceProjectionIndex: Contains the value of parameter epsilon;
epsilon - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj.AbstractSubspaceProjectionIndex.Factory: Contains the value of parameter epsilon;
epsilon - Variable in class de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj.AbstractSubspaceProjectionIndex.Factory.Parameterizer: Contains the value of parameter epsilon;
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.AbstractProjectedDBSCAN: Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to LocallyWeightedDistanceFunction.
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: 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: 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: 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.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.distance.distancefunction.subspace.AbstractPreferenceVectorBasedCorrelationDistanceFunction: Parameter to specify the maximum distance between two vectors with equal preference vectors before considering them as parallel, must be a double equal to or greater than 0.
EPSILON_ID - Static variable in class de.lmu.ifi.dbs.elki.index.preprocessed.localpca.RangeQueryFilteredPCAIndex.Factory: Parameter to specify the maximum radius of the neighborhood to be considered in the PCA, must be suitable to the distance function specified.
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,D extends Distance<D>> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan: The default DBSCAN and OPTICS neighbor predicate, using an epsilon-neighborhood.
EpsilonNeighborPredicate(D, DistanceFunction<O, D>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.EpsilonNeighborPredicate: Full constructor.
EpsilonNeighborPredicate.Instance<D extends Distance<D>> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan: Instance for a particular data set.
EpsilonNeighborPredicate.Instance(D, RangeQuery<?, D>, DBIDs) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.EpsilonNeighborPredicate.Instance: Constructor.
EpsilonNeighborPredicate.Parameterizer<O,D extends Distance<D>> - 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
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
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.DeLiClu.SpatialObjectPair: equals is used in updating the heap!
equals(Object) - Method in class de.lmu.ifi.dbs.elki.algorithm.outlier.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.RationalNumber: Two RationalNumbers are considered to be equal if both denominators and numerators are equal, respectively.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.data.SimpleClassLabel: Any ClassLabel should ensure a natural ordering that is consistent with equals.
equals(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.DistanceIntegerDBIDPair
equals(Object) - Method in class de.lmu.ifi.dbs.elki.database.ids.integer.DoubleDistanceIntegerDBIDPair
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: Simple equals statement.
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.ERiCDistanceFunction
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.PCABasedCorrelationDistanceFunction
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.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.LocallyWeightedDistanceFunction
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.MinKDistance
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.ProxyDistanceFunction
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.AbstractDimensionsSelectingDoubleDistanceFunction
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.AbstractPreferenceVectorBasedCorrelationDistanceFunction
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.DimensionSelectingDistanceFunction
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.distance.distancevalue.AbstractDistance: Returns true if this == o has the value true or o is not null and o is of the same class as this instance and this.compareTo(o) is 0, false otherwise.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancevalue.BitDistance
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancevalue.CorrelationDistance
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancevalue.DoubleDistance
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancevalue.FloatDistance
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancevalue.IntegerDistance
equals(Object) - Method in class de.lmu.ifi.dbs.elki.distance.distancevalue.SubspaceDistance
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.roc.ROC.DistanceResultAdapter: Deprecated.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.evaluation.roc.ROC.OutlierScoreAdapter: Deprecated.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.evaluation.roc.ROC.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: Returns true if this == o has the value true or o is not null and o is of the same class as this instance and the two index paths are of the same length, and contain the same components (.equals), false otherwise.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.index.tree.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.GenericDistanceSearchCandidate
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.TreeIndexPathComponent: Returns true if this == o has the value true or o is not null and o is of the same class as this instance and if the entry of this component equals the entry of the o argument, false otherwise.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix
equals(Object) - Method in class de.lmu.ifi.dbs.elki.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.result.optics.DoubleDistanceClusterOrderEntry: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class de.lmu.ifi.dbs.elki.result.optics.GenericClusterOrderEntry: 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.utilities.pairs.Triple: Canonical equals function
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(COPAC<V, IntegerDistance>) - 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
ERiCDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation: Provides a distance function for building the hierarchy in the ERiC algorithm.
ERiCDistanceFunction(IndexFactory<NumberVector<?>, FilteredLocalPCAIndex<NumberVector<?>>>, double, double) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.ERiCDistanceFunction: Constructor.
ERiCDistanceFunction.Instance<V extends NumberVector<?>> - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation: The actual instance bound to a particular database.
ERiCDistanceFunction.Instance(Relation<V>, FilteredLocalPCAIndex<V>, ERiCDistanceFunction, double, double) - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.ERiCDistanceFunction.Instance: Constructor.
ERiCDistanceFunction.Parameterizer - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation: Parameterization class.
ERiCDistanceFunction.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.ERiCDistanceFunction.Parameterizer
ERPDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.timeseries: Provides the Edit Distance With Real Penalty distance for FeatureVectors.
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_NOTSQUARE - Static variable in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: Error: matrix not square.
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
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.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
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.
estimators - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.AttributeWiseCDFNormalization: Stores the distribution estimators
estimators - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.normalization.AttributeWiseCDFNormalization.Parameterizer: Stores the distribution estimators
esucc - Variable in class de.lmu.ifi.dbs.elki.algorithm.clustering.OPTICSXi.SteepScanPosition: Next entry
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.
euclideanDistance(V, V) - Method in class de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.PCABasedCorrelationDistanceFunction.Instance: Computes the Euclidean distance between the given two vectors.
EuclideanDistanceFunction - Class in de.lmu.ifi.dbs.elki.distance.distancefunction.minkowski: Provides the Euclidean distance for FeatureVectors.
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
euclideanValue - Variable in class de.lmu.ifi.dbs.elki.distance.distancevalue.CorrelationDistance: The euclidean distance.
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.
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.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(Map<DBID, PROCLUS<V>.PROCLUSCluster>, Map<DBID, TIntSet>, Relation<V>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.PROCLUS: Evaluates the quality of the clusters.
evaluateOutlierResult(Database, OutlierResult) - Method in class de.lmu.ifi.dbs.elki.evaluation.histogram.ComputeOutlierHistogram: Evaluate a single outlier result as histogram.
EvaluateRankingQuality<V extends NumberVector<?>,D extends NumberDistance<D,?>> - Class in de.lmu.ifi.dbs.elki.algorithm.statistics: Evaluate a distance function with respect to kNN queries.
EvaluateRankingQuality(DistanceFunction<? super V, D>, int) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.statistics.EvaluateRankingQuality: Constructor.
EvaluateRankingQuality.Parameterizer<V extends NumberVector<?>,D extends NumberDistance<D,?>> - 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
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(HierarchicalResult, 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.
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
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: Flag to compute exact value range for binning.
exactGaussElimination() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: Perform an exact Gauss-elimination of this Matrix using RationalNumbers to yield highest possible accuracy.
exactGaussElimination(RationalNumber[][]) - Static method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: Perform recursive Gauss-elimination on the given matrix of RationalNumbers.
exactGaussJordanElimination() - Method in class de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix: Returns a matrix derived by Gauss-Jordan-elimination using RationalNumbers for the transformations.
exactMedian(Relation<V>, DBIDs, int) - Static method in class de.lmu.ifi.dbs.elki.utilities.DatabaseUtil: Returns the median of a data set in the given dimension.
exactMinMax(Relation<O>, DistanceQuery<O, D>) - 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.
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.
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
expandCluster(LocallyWeightedDistanceFunction.Instance<V>, RangeQuery<V, DoubleDistance>, DBID, FiniteProgress, IndefiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.AbstractProjectedDBSCAN: ExpandCluster function of DBSCAN.
expandCluster(Relation<O>, RangeQuery<O, D>, DBIDRef, FiniteProgress, IndefiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN: DBSCAN-function expandCluster.
expandCluster(int, WritableIntegerDataStore, T, FiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Instance: Set-based expand cluster implementation.
expandCluster(SimilarityQuery<O, IntegerDistance>, DBID, FiniteProgress, IndefiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.SNNClustering: DBSCAN-function expandCluster adapted to SNN criterion.
expandClusterOrder(ClusterOrderResult<D>, Database, RangeQuery<O, D>, DBID, D, FiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.OPTICS: OPTICS-function expandClusterOrder.
expandClusterOrderDouble(ClusterOrderResult<DoubleDistance>, Database, RangeQuery<O, DoubleDistance>, DBID, DoubleDistance, FiniteProgress) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.OPTICS: OPTICS-function expandClusterOrder.
expandDirNodes(SpatialPrimitiveDistanceFunction<NV, D>, DeLiCluNode, DeLiCluNode) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.DeLiClu: Expands the specified directory nodes.
expanded - Variable in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu.DeLiCluTree: Holds the ids of the expanded nodes.
expandLeafNodes(SpatialPrimitiveDistanceFunction<NV, D>, DeLiCluNode, DeLiCluNode, DataStore<KNNList<D>>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.DeLiClu: Expands the specified leaf nodes.
expandNode(O, DoubleDistanceKNNHeap, ComparableMinHeap<DoubleDistanceSearchCandidate>, double, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.DoubleDistanceRStarTreeKNNQuery
expandNode(O, KNNHeap<D>, ComparableMinHeap<GenericDistanceSearchCandidate<D>>, D, int) - Method in class de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query.GenericRStarTreeKNNQuery
expandNodes(DeLiCluTree, SpatialPrimitiveDistanceFunction<NV, D>, DeLiClu<NV, D>.SpatialObjectPair, DataStore<KNNList<D>>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.DeLiClu: Expands the spatial nodes of the specified pair.
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
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
EXPONENTS_ID - Static variable in class tutorial.distancefunction.MultiLPNorm.Parameterizer: Option ID for the exponents -multinorm.ps
exportItem - Variable in class de.lmu.ifi.dbs.elki.visualization.gui.ResultWindow: 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(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.
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.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: Class that turns a label column into an external ID column.
ExternalIDFilter(int) - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.ExternalIDFilter: Constructor.
ExternalIDFilter.Parameterizer - Class in de.lmu.ifi.dbs.elki.datasource.filter: Parameterization class.
ExternalIDFilter.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.datasource.filter.ExternalIDFilter.Parameterizer
externalIdIndex - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.ExternalIDFilter: The index of the label to be used as external Id.
externalIdIndex - Variable in class de.lmu.ifi.dbs.elki.datasource.filter.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.
externalizableSize() - Method in class de.lmu.ifi.dbs.elki.distance.distancevalue.BitDistance: Returns the number of Bytes this distance uses if it is written to an external file.
externalizableSize() - Method in class de.lmu.ifi.dbs.elki.distance.distancevalue.CorrelationDistance: Returns the number of Bytes this distance uses if it is written to an external file.
externalizableSize() - Method in interface de.lmu.ifi.dbs.elki.distance.distancevalue.Distance: Returns the number of Bytes this distance uses if it is written to an external file.
externalizableSize() - Method in class de.lmu.ifi.dbs.elki.distance.distancevalue.DoubleDistance: Returns the number of Bytes this distance uses if it is written to an external file.
externalizableSize() - Method in class de.lmu.ifi.dbs.elki.distance.distancevalue.FloatDistance: Returns the number of Bytes this distance uses if it is written to an external file.
externalizableSize() - Method in class de.lmu.ifi.dbs.elki.distance.distancevalue.IntegerDistance: Returns the number of Bytes this distance uses if it is written to an external file.
externalizableSize() - Method in class de.lmu.ifi.dbs.elki.distance.distancevalue.PreferenceVectorBasedCorrelationDistance: Returns the number of Bytes this distance uses if it is written to an external file.
externalizableSize() - Method in class de.lmu.ifi.dbs.elki.distance.distancevalue.SubspaceDistance: Returns the number of Bytes this distance uses if it is written to an external file.
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_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.
extractClusters(DBIDs, DBIDDataStore, DataStore<D>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.ExtractFlatClusteringFromHierarchy: Extract all clusters from the pi-lambda-representation.
extractClusters(ClusterOrderResult<N>, Relation<?>, double, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.OPTICSXi: Extract clusters from a cluster order result.
extractClusters(Relation<V>, DiSHDistanceFunction.Instance<V>, ClusterOrderResult<PreferenceVectorBasedCorrelationDistance>) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.DiSH: Extracts the clusters from the cluster order.
extractClustersDouble(DBIDs, DBIDDataStore, DoubleDistanceDataStore) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.ExtractFlatClusteringFromHierarchy: Extract all clusters from the pi-lambda-representation.
extractCorrelationClusters(Clustering<Model>, Relation<V>, int) - Method in class de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ERiC: Extracts the correlation clusters and noise from the copac result and returns a mapping of correlation dimension to maps of clusters within this correlation dimension.
ExtractFlatClusteringFromHierarchy<D extends Distance<D>> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical: Extract a flat clustering from a full hierarchy, represented in pointer form.
ExtractFlatClusteringFromHierarchy(HierarchicalClusteringAlgorithm<D>, int, ExtractFlatClusteringFromHierarchy.OutputMode, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.ExtractFlatClusteringFromHierarchy: Constructor.
ExtractFlatClusteringFromHierarchy(HierarchicalClusteringAlgorithm<D>, D, ExtractFlatClusteringFromHierarchy.OutputMode, boolean) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.ExtractFlatClusteringFromHierarchy: Constructor.
ExtractFlatClusteringFromHierarchy.CompareByDoubleLambda - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical: Order a DBID collection by the lambda value.
ExtractFlatClusteringFromHierarchy.CompareByDoubleLambda(DoubleDistanceDataStore) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.ExtractFlatClusteringFromHierarchy.CompareByDoubleLambda: Constructor.
ExtractFlatClusteringFromHierarchy.CompareByLambda<D extends Distance<D>> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical: Order a DBID collection by the lambda value.
ExtractFlatClusteringFromHierarchy.CompareByLambda(DataStore<D>) - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.ExtractFlatClusteringFromHierarchy.CompareByLambda: Constructor.
ExtractFlatClusteringFromHierarchy.OutputMode - Enum in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical: Output mode.
ExtractFlatClusteringFromHierarchy.OutputMode() - Constructor for enum de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.ExtractFlatClusteringFromHierarchy.OutputMode
ExtractFlatClusteringFromHierarchy.Parameterizer<D extends Distance<D>> - Class in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical: Parameterization class.
ExtractFlatClusteringFromHierarchy.Parameterizer() - Constructor for class de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.ExtractFlatClusteringFromHierarchy.Parameterizer
ExtractFlatClusteringFromHierarchy.ThresholdMode - Enum in de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical: Threshold mode.
ExtractFlatClusteringFromHierarchy.ThresholdMode() - Constructor for enum de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.ExtractFlatClusteringFromHierarchy.ThresholdMode
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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