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E

elki.evaluation.outlier - package elki.evaluation.outlier

Evaluate an outlier score using a misclassification based cost model.

elki.evaluation.scores.adapter - package elki.evaluation.scores.adapter

elki.outlier - package elki.outlier

Outlier detection algorithms.

elki.outlier.anglebased - package elki.outlier.anglebased

Angle-based outlier detection algorithms.

elki.outlier.density - package elki.outlier.density

Density-based outlier detection algorithms.

elki.outlier.distance - package elki.outlier.distance

Distance-based outlier detection algorithms, such as DBOutlier and kNN.

elki.outlier.distance.parallel - package elki.outlier.distance.parallel

Parallel implementations of distance-based outlier detectors.

elki.outlier.intrinsic - package elki.outlier.intrinsic

Outlier detection algorithms based on intrinsic dimensionality.

elki.outlier.lof - package elki.outlier.lof

LOF family of outlier detection algorithms.

elki.outlier.lof.parallel - package elki.outlier.lof.parallel

Parallelized variants of LOF.

elki.outlier.meta - package elki.outlier.meta

Meta outlier detection algorithms: external scores, score rescaling.

elki.outlier.spatial - package elki.outlier.spatial

Spatial outlier detection algorithms.

elki.outlier.spatial.neighborhood - package elki.outlier.spatial.neighborhood

Spatial outlier neighborhood classes.

elki.outlier.spatial.neighborhood.weighted - package elki.outlier.spatial.neighborhood.weighted

Weighted neighborhood definitions.

elki.outlier.subspace - package elki.outlier.subspace

Subspace outlier detection methods.

elki.outlier.trivial - package elki.outlier.trivial

Trivial outlier detection algorithms: no outliers, all outliers, label outliers.

elki.result.outlier - package elki.result.outlier

Outlier result classes.

elki.utilities.scaling.outlier - package elki.utilities.scaling.outlier

Scaling of outlier scores, that require a statistical analysis of the occurring values.

end - Variable in class elki.outlier.density.HySortOD.TreeStrategy.Node

Index information.

eps - Variable in class elki.outlier.subspace.OUTRES

The epsilon (in 2d) parameter

eps - Variable in class elki.outlier.subspace.OUTRES.Par

Query radius

epsilons - Variable in class elki.outlier.subspace.OUTRES.KernelDensityEstimator

Epsilon values for different subspace dimensionalities

equals(Object) - Method in class elki.outlier.density.HySortOD.Hypercube

equals(Object) - Method in class elki.outlier.subspace.AggarwalYuEvolutionary.Individuum

estimateDensities(Relation<O>, KNNSearcher<DBIDRef>, DBIDs, WritableDataStore<double[]>) - Method in class elki.outlier.lof.KDEOS

Perform the kernel density estimation step.

estimateID(DBIDRef, DoubleDBIDListIter, double[]) - Method in class elki.outlier.intrinsic.ISOS

Estimate the local intrinsic dimensionality.

estimateInitialBeta(DBIDRef, DoubleDBIDListIter, double) - Static method in class elki.outlier.distance.SOS

Estimate beta from the distances in a row.

estimator - Variable in class elki.outlier.intrinsic.IDOS

Estimator for intrinsic dimensionality.

estimator - Variable in class elki.outlier.intrinsic.IDOS.Par

Estimator for intrinsic dimensionality.

estimator - Variable in class elki.outlier.intrinsic.ISOS

Estimator of intrinsic dimensionality.

estimator - Variable in class elki.outlier.intrinsic.LID

Estimator for intrinsic dimensionality.

estimator - Variable in class elki.outlier.intrinsic.LID.Par

Estimator for intrinsic dimensionality.

ESTIMATOR_ID - Static variable in class elki.outlier.intrinsic.IDOS.Par

The class used for estimating the intrinsic dimensionality.

ESTIMATOR_ID - Static variable in class elki.outlier.intrinsic.LID.Par

Class to use for estimating the ID.

evaluate(EvaluationResult, int, int, Supplier<ScoreEvaluation.Adapter>) - Method in class elki.evaluation.outlier.OutlierRankingEvaluation

Produce various evaluation statistics

evaluateBy(ScoreEvaluation) - Method in class elki.result.outlier.OutlierResult

Evaluate given a set of positives and a scoring.

evaluateOutlierResult(Database, OutlierResult) - Method in class elki.evaluation.outlier.ComputeOutlierHistogram

Evaluate a single outlier result as histogram.

EvolutionarySearch(Relation<? extends NumberVector>, ArrayList<ArrayList<DBIDs>>, Random) - Constructor for class elki.outlier.subspace.AggarwalYuEvolutionary.EvolutionarySearch

Constructor.

expect - Variable in class elki.outlier.COP

Expected amount of outliers.

expect - Variable in class elki.outlier.COP.Par

Expected amount of outliers.

EXPECT_ID - Static variable in class elki.outlier.COP.Par

Expected share of outliers.

ExtendedNeighborhood - Class in elki.outlier.spatial.neighborhood

Neighborhood obtained by computing the k-fold closure of an existing neighborhood.

ExtendedNeighborhood(DataStore<DBIDs>) - Constructor for class elki.outlier.spatial.neighborhood.ExtendedNeighborhood

Constructor.

ExtendedNeighborhood.Factory<O> - Class in elki.outlier.spatial.neighborhood

Factory class.

ExtendedNeighborhood.Factory.Par<O> - Class in elki.outlier.spatial.neighborhood

Parameterization class.

extendNeighborhood(Database, Relation<? extends O>) - Method in class elki.outlier.spatial.neighborhood.ExtendedNeighborhood.Factory

Method to load the external neighbors.

ExternalDoubleOutlierScore - Class in elki.outlier.meta

External outlier detection scores, loading outlier scores from an external file.

ExternalDoubleOutlierScore(URI, Pattern, Pattern, boolean, ScalingFunction) - Constructor for class elki.outlier.meta.ExternalDoubleOutlierScore

Constructor.

ExternalDoubleOutlierScore.Par - Class in elki.outlier.meta

Parameterization class

ExternalNeighborhood - Class in elki.outlier.spatial.neighborhood

A precomputed neighborhood, loaded from an external file.

ExternalNeighborhood(DataStore<DBIDs>) - Constructor for class elki.outlier.spatial.neighborhood.ExternalNeighborhood

Constructor.

ExternalNeighborhood.Factory - Class in elki.outlier.spatial.neighborhood

Factory class.

ExternalNeighborhood.Factory.Par - Class in elki.outlier.spatial.neighborhood

Parameterization class.

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